To see the other types of publications on this topic, follow the link: Mathematics|Biomedical engineering|Medicine.
Journal articles on the topic 'Mathematics|Biomedical engineering|Medicine'
Create a spot-on reference in APA, MLA, Chicago, Harvard, and other styles
Consult the top 46 journal articles for your research on the topic 'Mathematics|Biomedical engineering|Medicine.'
Next to every source in the list of references, there is an 'Add to bibliography' button. Press on it, and we will generate automatically the bibliographic reference to the chosen work in the citation style you need: APA, MLA, Harvard, Chicago, Vancouver, etc.
You can also download the full text of the academic publication as pdf and read online its abstract whenever available in the metadata.
Browse journal articles on a wide variety of disciplines and organise your bibliography correctly.
1
King, P. "Mathematics and Physics of Emerging Biomedical Imaging [Book Reviews]." IEEE Engineering in Medicine and Biology Magazine 15, no. 5 (1996): 141. http://dx.doi.org/10.1109/memb.1996.537074.
Full text
2
Ciaccio, E. J. "Mathematics and Physics of Emerging Biomedical Imaging [Book Reviews]." IEEE Engineering in Medicine and Biology Magazine 15, no. 6 (1996): 136. http://dx.doi.org/10.1109/memb.1996.544522.
Full text
3
Suhir, Ephraim. "Crossing the Lines." Mechanical Engineering 126, no. 09 (2004): 39. http://dx.doi.org/10.1115/1.2004-sep-2.
Full textAbstract:
It is important that today’s outstanding engineer must have knowledge of many sciences and disciplines. Interdisciplinary skills help an engineer to cope with the changing social, economic, and political conditions that influence technology and its development. Nanotechnology and biotechnology remind us how important it is to be knowledgeable in many areas of applied science and engineering. A nanotechnology engineer should be well familiar with physics, materials science, surface chemistry, composites, quantum mechanics, materials, and mathematics. Biotechnology merges physics, engineering, and chemistry with biology, life sciences, and medicine. The multifaceted approach helps define and resolve problems in biomedical research and in clinical medicine for improved healthcare. The most surprising discoveries have been made at the boundaries of different disciplines. Alessandro Volta’s electric battery was a meeting of chemistry and physics.
4
Dietert, Rodney R. "Integrating Contemplative Tools into Biomedical Science Education and Research Training Programs." Journal of Biomedical Education 2014 (July 2, 2014): 1–11. http://dx.doi.org/10.1155/2014/239348.
Full textAbstract:
Academic preparation of science researchers and/or human or veterinary medicine clinicians through the science, technology, engineering, and mathematics (STEM) curriculum has usually focused on the students (1) acquiring increased disciplinary expertise, (2) learning needed methodologies and protocols, and (3) expanding their capacity for intense, persistent focus. Such educational training is effective until roadblocks or problems arise via this highly-learned approach. Then, the health science trainee may have few tools available for effective problem solving. Training to achieve flexibility, adaptability, and broadened perspectives using contemplative practices has been rare among biomedical education programs. To address this gap, a Cornell University-based program involving formal biomedical science coursework, and health science workshops has been developed to offer science students, researchers and health professionals a broader array of personal, contemplation-based, problem-solving tools. This STEM educational initiative includes first-person exercises designed to broaden perceptional awareness, decrease emotional drama, and mobilize whole-body strategies for creative problem solving. Self-calibration and journaling are used for students to evaluate the personal utility of each exercise. The educational goals are to increase student self-awareness and self-regulation and to provide trainees with value-added tools for career-long problem solving. Basic elements of this educational initiative are discussed using the framework of the Tree of Contemplative Practices.
5
Sharma, Manish Kumar, and Rashmi Gupta. "Nanorobotics: The Future of Medicines." Research in Pharmacy and Health Sciences 2, no. 1 (2016): 51–56. http://dx.doi.org/10.32463/rphs.2016.v02i01.10.
Full textAbstract:
Nano-robots are the technology of creating machines or robots close to the microscopic scale to nanometer. Nano-robots is a truly multidisciplinary field which comprises of the simultaneous advantage of medicinal and robots knowledge disciplines will merge including robots, and mechanical, chemical and biomedical engineering, chemistry, biology, physical science and mathematics or arithmetic. Nano-robots medicine is therapeutically more effective, individualized, dose reduced and more affordable medicine. Nano-robots medicines are being developed to improve drug bioavailability. Target drug delivery is currently the most advanced application of Nano-robots in medicine. Nanotechnology is being used to produce new generations of biomaterial scaffolds that can encourage or support cell growth and differentiation into often complex tissue types. Nano-robots medicine include targeting semi-metallic or metallic nanoparticles, e.g. silica, iron or gold, to tumor sites and then activating them by external means, e.g. light, magnetic field, ultrasound, to produce heat or soft radiation locally that can destroy the cancer cells in situ gene therapy cell therapy. Nano medicines are better imaging-techniques and other diagnostic tools Nano-robots opens up new ways for vast and abundant research work in which many. Nanorobots have strong potential to revolutionize healthcare to treat disease in future.
6
Jordan, Joanne L. "PubMed Central: An Essential Resource for Information Professionals and Researchers." Evidence Based Library and Information Practice 8, no. 2 (2013): 261. http://dx.doi.org/10.18438/b80p5j.
Full textAbstract:
Objective – A review of the journals containing research listed in PubMed Central (PMC), but not selected for inclusion in the National Library of Medicine (NLM) collection. The authors identified reasons why journals had not been included in the collection and if any met the NLM selection criteria and were appropriate for inclusion.
 
 Design – Descriptive study.
 
 Setting – National Library of Medicine, United States.
 
 Subjects – 571 journals that were not included in the NLM collection but had research articles in PMC.
 Methods – In October 2009, a report was produced from the NLM library system listing journals tagged as having articles in PMC and not being in the NLM collection. Information was gathered on the journals identified and these were checked against the Collection Development Manual of the NLM and the NLM checklist used for selecting electronic journals. The reason for non-selection of the journal was recorded and the subject category, according to the Library of Congress Classification, was noted.
 
 Recorded reasons why journals were not selected:
 
 • Less than 15% of articles were within scope of NLM collection
 • Not enough articles published
 • Coverage (lacking original research or not for a scholarly audience)
 • Insufficient information to determine reason
 
 For journals where the criteria seemed to be met, the decision on selection to the NLM collection was reviewed.
 
 Main Results – The authors identified 571 journals that had articles in PMC but did not meet the criteria for inclusion in the NLM journal collection. The majority of these journals (73%) were outside the NLM scope and a further 10% had not published a sufficient number of articles to be considered. A further 3% were assessed as not intended for a scholarly audience or lacked original research and another 3% could not be reviewed due to lack of information available. There were 65 journals (11%) that were referred for further review as the selection criteria seemed to be met and 11 of these journals have subsequently been added to the NLM collection. This is in relation to 482 new print and electronic journals in total that were added to the NLM collection in 2009.
 
 However, only 369 of the 571 journals (65%) had one or more articles included in PMC; of these, 238 had one article and 33 had more than four articles in the archive. The reason that some journals had no articles in PMC at the time of this review was due to the time it takes to process new articles and embargos set by the publishers that restrict immediate listing on open access databases such as PMC. A number of these journals may also be new and may not have had a sufficient number of articles or enough information available to be able to include them in the NLM collection. To add context, the authors state that PMC contained over 115,000 NIH-funded articles by the end of November 2010.
 
 The subject areas these non-selected journals were classified under included Engineering (15%); Medicine (14%); Mathematics (10%); Chemistry (10%); and Computer Science (9%). Library Science was assigned to 2% of the journals. The Medicine journals were more likely than those in the other subject areas to be new journals without sufficient articles to be included in the NLM collection.
 
 Conclusion – When the journal title is out of the scope of the NLM collection, an individual article in that journal can still be included in PMC. This provides a solution to the problem of how to collect biomedical research that is not published in biomedical journals. This may be more important in the future as the field becomes more interdisciplinary. This also provides a useful resource for libraries and researchers searching for full-text biomedical articles.
 
 The authors conclude that analyzing the articles from the journals not selected for inclusion in the NLM collection will provide helpful information about the types of biomedical research being published in non-biomedical journals. This will highlight particular areas the NLM should pay attention to in the future.
7
Sens, Donald A., Karen L. Cisek, Scott H. Garrett, et al. "STEERing an IDeA in Undergraduate Research at a Rural Research Intensive University." Academic Pathology 4 (January 1, 2017): 237428951773509. http://dx.doi.org/10.1177/2374289517735092.
Full textAbstract:
This study documents outcomes, including student career choices, of the North Dakota Institutional Development Award Networks of Biomedical Research Excellence program that provides 10-week, summer undergraduate research experiences at the University of North Dakota School of Medicine and Health Sciences. Program evaluation initiated in 2008 and, to date, 335 students have completed the program. Of the 335, 214 students have successfully completed their bachelor’s degree, 102 are still undergraduates, and 19 either did not complete a bachelor’s degree or were lost to follow-up. The program was able to track 200 of the 214 students for education and career choices following graduation. Of these 200, 76% continued in postgraduate health-related education; 34.0% and 20.5% are enrolled in or have completed MD or PhD programs, respectively. Other postbaccalaureate pursuits included careers in pharmacy, optometry, dentistry, public health, physical therapy, nurse practitioner, and physician’s assistant, accounting for an additional 21.5%. Most students electing to stop formal education at the bachelor’s degree also entered fields related to health care or science, technology, engineering, and mathematics (19.5%), with only a small number of the 200 students tracked going into service or industries which lacked an association with the health-care workforce (4.5%). These student outcomes support the concept that participation in summer undergraduate research boosts efforts to populate the pipeline of future researchers and health professionals. It is also an indication that future researchers and health professionals will be able to communicate the value of research in their professional and social associations. The report also discusses best practices and issues in summer undergraduate research for students originating from rural environments.
8
Shruthishree and Harshvardhan Tiwari. "A REVIEW PAPER ON MEDICAL IMAGE PROCESSING." International Journal of Research -GRANTHAALAYAH 5, no. 4RACSIT (2017): 21–29. http://dx.doi.org/10.29121/granthaalayah.v5.i4racsit.2017.3344.
Full textAbstract:
Biomedical image processing has experienced dramatic expansion, and has been an interdisciplinary research field attracting expertise from applied mathematics, computer sciences, engineering, statistics, physics, biology and medicine. Computer-aided diagnostic processing has already become an important part of clinical routine. Accompanied by a rush of new development of high technology and use of various imaging modalities, more challenges arise; for example, how to process and analyze a significant volume of images so that high quality information can be produced for disease diagnoses and treatment. The principal objectives of this course are to provide an introduction to basic concepts and techniques for medical image processing and to promote interests for further study and research in medical imaging processing.The rapid progress of medical science and the invention of various medicines have benefited mankind and the whole civilization. Modern science also has been doing wonders in the surgical field. But, the proper and correct diagnosis of diseases is the primary necessity before the treatment. The more sophisticate the bio-instruments are, better diagnosis will be possible. The medical image plays an important role in clinical diagnosis and therapy of doctor and teaching and researching etc. Medical imaging is often thought of as a way to represent anatomical structures of the body with the help of X-ray computed tomography and magnetic resonance imaging. But often it is more useful for physiologic function rather than anatomy. With the growth of computer and image technology medical imaging has greatly influenced medical field. As the quality of medical imaging affects diagnosis the medical image processing has become a hotspot and the clinical applications wanting to store and retrieve images for future purpose needs some convenient process to store those images in details.
9
Hardy, Elaissa L., Brenda Williams, Christopher Harden, et al. "STEM Education for Children with Sickle Cell Disease: Unique Educational Outreach Program Taught By Near-Peer Undergraduate Students." Blood 136, Supplement 1 (2020): 12–13. http://dx.doi.org/10.1182/blood-2020-142018.
Full textAbstract:
One fifth of school aged children in the US have a chronic medical illness and represent an underserved and educationally disadvantaged population. In particular, children with sickle cell disease (SCD) of all genotypes spend significant amounts of time in the medical settings and represent a potentially "captive audience" where hospitalization time can include educational activities. Accordingly, we saw an opportunity for Biomedical Engineering (BME) undergraduates at Georgia Institute of Technology, who are taught biology, medicine, engineering, and design to implement a new paradigm of K-12 Science, Technology, Engineering, and Mathematics (STEM) programming, where human physiology is used as a model framework. In collaboration with hospital school teachers at Children's Healthcare of Atlanta, we created a novel educational program where we (1) leverage the patient's own medical experience as motivation for learning, (2) develop hands-on interactive activities to teach STEM concepts that are adaptable for the patient's cognitive level, (3) provide undergraduate students with high quality meaningful patient interactions and clinical experiences, and (4) provide innovative educational programming for hospitals. The BME undergraduates enrolled in a human-centered design course focusing on iterative design, development and implementation of hands-on interactive STEM activities rooted in human physiology (Fig. 1A). Each activity contains state and national K-12 STEM standards. The BME undergraduates are well-suited to teach in the hospital environment, as they experience a strong STEM curriculum and are able to capture the true interdisciplinary nature of medical science in each activity. The undergraduates and patients are near-peer age, relationship-building occurs quickly, the patients admire them and enjoy their time together. During the 2018-19 school year we developed learning assessment questions for 2 of the most requested activities, assessing each SCD patient's mastery of the learning objectives. In the Blood Jar activity (Fig. 1B), the SCD patient builds a model of blood, learning the composition, function of each component, and importance of hydration. Sixty-five patients participated, 43% of grade K - 2, 61% of 3 - 5, 85% of 6th through High School scored Thoroughly Demonstrated. In the Bone activity (Fig. 1C), each SCD patient constructs a bone model to understand the function and structure of a bone. Twenty-nine patients participated, 28% of grade K - 2, 30% of 3 - 5, 88% of 6 - 8, and 75% of high school scored Thoroughly Demonstrated. Patient feedback (Fig. 1D) has been overwhelmingly positive, stating the activities are "fun" and "engaging" and requesting additional visits from the BME undergraduates. BME undergraduate expressed growth and learning of: disease pathophysiology, teaching and learning styles, and effective and succinct communication skills. In Georgia, Life Science is taught in 5th and 7th grade, our target demographic. Our results show at least 75% of patients in 6th grade and above demonstrated thorough understanding of the STEM topics taught, while K - 5 grade did not achieve that level of understanding. Lower scores for those patients are attributed to difficulties remembering new scientific vocabulary. Many of the BME undergraduates in our program are pre-med and use the experiences and meaningful interactions with patients in their medical school applications. As stated by a BME undergraduate after a patient interaction, "the white blood cells are like soldiers in the army! I like that! This analogy prompted the patient to think of his future. It reminded me the littlest things can make a big difference. This makes me even more excited to go into medicine." Our program represents an innovative approach to teaching STEM by: engaging SCD children, who are uniquely suited to learn important STEM concepts within the context of their own disease, provide learning to SCD patients during extended absences from school, allowing BME undergraduate students to design, develop, and teach STEM activities, provide meaningful clinical experience, and supplying quality educational programming for the hospital. This collaborative program can be straightforwardly implemented at other pediatric institutions with robust college volunteer programs and hospital school programs. Our activities can be exported and implemented at other institutions. Disclosures Lam: Sanguina, Inc: Current equity holder in private company.
10
Humphrey, J. D., G. L. Coté, J. R. Walton, G. A. Meininger, and G. A. Laine. "A new paradigm for graduate research and training in the biomedical sciences and engineering." Advances in Physiology Education 29, no. 2 (2005): 98–102. http://dx.doi.org/10.1152/advan.00053.2004.
Full textAbstract:
98Emphasis on the individual investigator has fostered discovery for centuries, yet it is now recognized that the complexity of problems in the biomedical sciences and engineering requires collaborative efforts from individuals having diverse training and expertise. Various approaches can facilitate interdisciplinary interactions, but we submit that there is a critical need for a new educational paradigm for the way that we train biomedical engineers, life scientists, and mathematicians. We cannot continue to train graduate students in isolation within single disciplines, nor can we ask any one individual to learn all the essentials of biology, engineering, and mathematics. We must transform how students are trained and incorporate how real-world research and development are done–in diverse, interdisciplinary teams. Our fundamental vision is to create an innovative paradigm for graduate research and training that yields a new generation of biomedical engineers, life scientists, and mathematicians that is more diverse and that embraces and actively pursues a truly interdisciplinary, team-based approach to research based on a known benefit and mutual respect. In this paper, we describe our attempt to accomplish this via focused training in biomechanics, biomedical optics, mathematics, mechanobiology, and physiology. The overall approach is applicable, however, to most areas of biomedical research.
11
Wilmut, Ian, Tuempong Wongtawan, Mindy Quigley, and Gareth Sullivan. "Biomedical and social contributions to sustainability." Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences 369, no. 1942 (2011): 1730–47. http://dx.doi.org/10.1098/rsta.2010.0370.
Full textAbstract:
Over the past two or three centuries, biomedical advances have provided methods to prevent and treat infectious diseases. These changes have greatly reduced human suffering and enhanced sustainability by allowing people to live longer and healthier lives. The challenge for the coming centuries will be to ensure that these longer, healthier lives are also more productive lives. We must build on the gains of the past by translating new discoveries in regenerative medicine into therapies for degenerative and genetic diseases. Stem cells may be used to identify drugs that prevent the development of symptoms or to replace cells that have either died or lost their physiological function. In the case of genetic diseases, it may be possible to correct the genetic error. While most conditions that might be treated in these ways are common to all communities, some are more prevalent in specific races. Provision of these and other benefits depends not only on attainment of the research objectives, but also upon our ability to make treatment opportunities available throughout both developed and developing communities. The long history of researching and treating infectious diseases shows that it may take many decades to reap the full benefit of the new biological understanding.
12
Murray, J. D. "Vignettes from the field of mathematical biology: the application of mathematics to biology and medicine." Interface Focus 2, no. 4 (2012): 397–406. http://dx.doi.org/10.1098/rsfs.2011.0102.
Full textAbstract:
The application of mathematical models in biology and medicine has a long history. From the sparse number of papers in the first half of the twentieth century with a few scientists working in the field it has become vast with thousands of active researchers. We give a brief, and far from definitive history, of how some parts of the field have developed and how the type of research has changed. We describe in more detail just two examples of specific models which are directly related to real biological problems, namely animal coat patterns and the growth and image enhancement of glioblastoma brain tumours.
13
Oppenheimer, Steven B., Jack I. Mills, Ali Zakeri, Trista R. Payte, Avi Lidgi, and MariaElena Zavala. "An Approach to Improving Student Success in Science, Technology, Engineering, and Mathematics (STEM ) Career Pathways." Ethnicity & Disease 30, no. 1 (2020): 33–40. http://dx.doi.org/10.18865/ed.30.1.33.
Full textAbstract:
In this article, we report on an 11-year study that explores approaches to improve student success in college by a five-week summer program in Mathematics and Language Arts for entering freshmen. To recruit students into the program, we invited students accepted at the university and listed as underrepresented and economically disadvantaged (Pell-eligible) by the Office of Institutional Research at California State University, Northridge. The program consisted of all-day Math and English enhancement in mixed ability groups. Results of this program examining Math and English performance at California State University, Northridge showed that students completing the summer programs during the 11-year study period had improved pass rates in Math and English at California State University, Northridge compared with students in a control group who did not participate in the summer program. The results show that intensive pre-college enhancement for entering freshmen can improve student success in college. Student graduation data from the early cohorts (2010, 2011, 2012) were obtained from Institutional Research. The summary results showed that students from the accepted/ attending group had substantially increased GPAs and graduation rates, essentially closing the achievement gap. Increased interest in biomedical research careers was also developed by the program, as demonstrated by a five-fold number of summer enrichment participants entering the PhD, MARC (Minority Access to Research Careers) and RISE (Research Initiative for Scientific Enhancement) programs than students who did not attend summer enrichment. Ethn Dis.2020;30(1):33-40; doi:10.18865/ed.30.1.33
14
Клышников, К. Ю., and K. U. Klyshnikov. "Modeling of the Hemodynamics of Vascular Prostheses "Kemangiprotez" in Silico." Mathematical Biology and Bioinformatics 12, no. 2 (2017): 559–69. http://dx.doi.org/10.17537/2017.12.559.
Full textAbstract:
The paper describes aspects of the application of numerical simulation of fluid flows in clinical medicine with interventions on the human vascular system. The modeling method used in the study is verified using the data of the doppler sonography of the patient underwent vascular replacement. It was shown that the deviation between the numerical experiment and the clinical data - pressure curves at the inlet and outlet of the studied vessel, is 20%. The obtained quantitative characteristics of the flow: peak systolic velocity, final diastolic velocity, minimum diastolic velocity, resistivity index, pulsatility index, systole/diastole index are comparable between verification and experimental data. Thus, for the proximal site of the clinical vessel the corresponding indices were 96.5 cm/s; 4.5 cm/s; 36.2 cm/s; 1.05; 11.5; 21.3. For simulation, 107.9 cm/s; 4.44 cm/s; 43.9 cm/s; 1.05; 12.0; 24.3. In addition, the work describes the application of tested method in two clinical vascular prostheses "KemAngioprotez" for the assessment of zones of increased shear stress and, thus, the risk of thrombus formation. It is shown that the distribution of critical zones corresponds to zones of anastomosis between prosthesis segments, which may be a potential location for optimization of the device.
15
Korshakov, A. V. "Brain-Computer Interface Systems Based On the Near-Infrared Spectroscopy." Mathematical Biology and Bioinformatics 13, no. 1 (2018): 84–129. http://dx.doi.org/10.17537/2018.13.84.
Full textAbstract:
The article describes the modern systems of man and computer interaction, or Brain-Computer Interfaces (BCIs), of several types. The interfaces, based on hemodynamic activity measurements of human cerebral cortex by the means of the near-infrared spectroscopy are discussed and also those, which are based on the combinations of the near-infrared spectroscopy, the electroencephalography and the encephalographies of other modalities. The theoretical fundamentals are provided of near-infrared spectroscopy devices functioning and a number of the typical experiments in the field noted. The special focus is on the functional magnetic resonance imaging and other methods of collecting biometrics data in the context of hemodynamic response . Various practical realizations and technical solutions of devices of mentioned type are described. The highlight of possible practical utilizations of human-machine interfaces in the sphere of medicine and/or medical rehabilitation is given. The analysis of practical solutions and applications of BCI systems is performed, which was added by a systematic publications review . Related disciplines have been also considered. Several examples of simultaneous usage of BCIs and robotics systems, which were built for the compensation of human body's lost functions also are provided. Some attention is paid to the Fast Optical Signals and to the researches in the field of optogenetics. The results of the conducted research make us to believe that the peeked field of knowledge is fairly young and at some areas of it the process of pure research and random search of new facts and technical solutions is still ongoing, although with an extremely high intensity. All things considered, the analised research direction should be judged as highly perspective, all the more so as it is joined with wide area of related disciplines with broad spectra of implementations.
16
Sokolov, A. V., V. K. Bolondinsky, and V. V. Voloshinov. "Technology of Balanced Identification for Selection of Pine Transpiration Mathematical Model." Mathematical Biology and Bioinformatics 14, no. 2 (2019): 665–82. http://dx.doi.org/10.17537/2019.14.665.
Full textAbstract:
The application of numerical technology for evaluation the correspondence of a mathematical model and experimental data via the balanced (optimization) identification method is demonstrated with comparing various models of pine transpiration. A quantitative measure of the model evaluation is the cross-validation error. Current implementation of the technology allow the researcher to formulate the computing task in a text file, which contains: mathematical model formulas (including differential and/or integration equations); declarations of parameters and/or functions to be identified; data source (with experimental measurements) and additional settings of the numerical method. As a result, the software package returns unknown parameters, functions, and modeling errors. This technology is successfully used to various models in biology, medicine, physics, etc.
17
Miller, Karol. "Computational biomechanics for medicine." International Journal for Numerical Methods in Biomedical Engineering 27, no. 3 (2011): 345–46. http://dx.doi.org/10.1002/cnm.1434.
Full text
18
Sanz-Herrera, J. A., J. M. García-Aznar, and M. Doblaré. "A mathematical approach to bone tissue engineering." Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences 367, no. 1895 (2009): 2055–78. http://dx.doi.org/10.1098/rsta.2009.0055.
Full textAbstract:
Tissue engineering is becoming consolidated in the biomedical field as one of the most promising strategies in tissue repair and regenerative medicine. Within this discipline, bone tissue engineering involves the use of cell-loaded porous biomaterials, i.e. bioscaffolds, to promote bone tissue regeneration in bone defects or diseases such as osteoporosis, although it has not yet been incorporated into daily clinical practice. The overall success of a particular bone tissue engineering application depends strongly on scaffold design parameters, which do away with long and expensive clinical protocols. Computer simulation is a useful tool that may reduce animal experiments and help to identify optimal patient-specific designs after concise model validation. In this paper, we present a novel mathematical approach to bone regeneration within scaffolds, based on a multiscale framework. Results are presented over an actual scaffold microstructure, showing the potential of computer simulation, and how it can aid in the task of making bone tissue engineering a reality in clinical practice.
19
Chen, Hu, Bo Song, and Longkun Li. "A Novel Noninvasive Topological Mathematical Nomogram for Diagnosing Male Bladder Outflow Obstruction." Journal of Biomaterials and Tissue Engineering 9, no. 9 (2019): 1205–10. http://dx.doi.org/10.1166/jbt.2019.2119.
Full textAbstract:
Currently the pressure–flow (P/Q) study is considered as the golden standard for diagnosing bladder outflow obstruction (BOO), with clear invasion. In this study we established a novel topological mathematical nomogram with noninvasive free uroflow metry for predicting BOO. Based on the Hill model of topological mathematics, the detrusor contractility (DC) and, the rates of detrusor contraction velocity variation (RDCVV) of the bladder were acquired. An RDCVV less than 0.2 were considered suitable for the DC/maximum uroflow (C/Q) study. A C/Q nomogram was established via 233 cases (22 unobstructed, 49 equivocal, and 162 obstructed according to an invasive pressure/ uroflow study) with an RDCVV less than 0.2. Moreover, the C/Q nomogram was verified with 522 suitable cases with RDCVV less than 0.2 (328 obstructed, 106 equivocal, and 88 unobstructed according to an invasive pressure/uroflow study). A C/Q nomogram was successfully established and verified that have a high precision. A novel topological mathematical C/Q nomogram with noninvasive free uroflowmetry was successfully established for predicting BOO in male, with relatively high accuracy.
20
van Berlo, Ad MW, R. R. Parchen, P. H. van Rjsingen, K. H. Massen, and Ad H. M. Verkooyen. "Kinetic Modeling of Powder Charcoal Haemoperfusion." International Journal of Artificial Organs 9, no. 5 (1986): 313–18. http://dx.doi.org/10.1177/039139888600900510.
Full textAbstract:
The aim of this study was to achieve more understanding of the mass transfer characteristics of the filmadsorber haemoperfusion device. First, a structural model with mathematical description of the different diffusion steps was developed. Exact quantification appeared very difficult, resulting in insufficient fit of predicted and measured concentration curves. Moreover, the mathematics turned out simple, since the concentration courses could be described with one exponential power. Therefore, a formal model was developed, assuming linear isotherms and adsorption, proportional to the average concentration in the column. With this model predicted in-vitro inlet and outlet concentrations could be fitted to the measured data accurately. A relation between both models is given under the condition of high intraparticle mass transfer, which is allowed in case of powder adsorbents. It can be concluded that structural models do not yield predictive tools for optimization of device geometry. A formal model with two constants determining device performance enables device optimization with the help of some in-vitro experiments.
21
Pérez-Medina, Carlos, Sjoerd Hak, Thomas Reiner, Zahi A. Fayad, Matthias Nahrendorf, and Willem J. M. Mulder. "Integrating nanomedicine and imaging." Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences 375, no. 2107 (2017): 20170110. http://dx.doi.org/10.1098/rsta.2017.0110.
Full textAbstract:
Biomedical engineering and its associated disciplines play a pivotal role in improving our understanding and management of disease. Motivated by past accomplishments, such as the clinical implementation of coronary stents, pacemakers or recent developments in antibody therapies, disease management now enters a new era in which precision imaging and nanotechnology-enabled therapeutics are maturing to clinical translation. Preclinical molecular imaging increasingly focuses on specific components of the immune system that drive disease progression and complications, allowing the in vivo study of potential therapeutic targets. The first multicentre trials highlight the potential of clinical multimodality imaging for more efficient drug development. In this perspective, the role of integrating engineering, nanotechnology, molecular imaging and immunology to yield precision medicine is discussed. This article is part of the themed issue ‘Challenges for chemistry in molecular imaging’.
22
Cormack, A. N., and A. Tilocca. "Structure and biological activity of glasses and ceramics." Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences 370, no. 1963 (2012): 1271–80. http://dx.doi.org/10.1098/rsta.2011.0371.
Full textAbstract:
Biomaterials for repairing and regenerating parts of the human body play a key role in contemporary medicine, and have an increasing impact in modern society. Given the importance of orthopaedic medicine (bone is the second most replaced organ after blood), bioactive glasses and ceramics represent a key reference to guide technological advances in this field. Their established role in current biomedical applications has already led many research groups worldwide to look into their structural properties, with a view to identifying the molecular basis of their biological activity. As the efforts directed towards this crucial and exciting direction continue to increase, it is now timely to review the situation, in order to guide future investigations on structure–bioactivity relationships. In this introductory article, the field is reviewed, to provide an appropriate context for the contributions to this Theme Issue.
23
Adams, Kim D., and Albert M. Cook. "Performing mathematics activities with non-standard units of measurement using robots controlled via speech-generating devices: three case studies." Disability and Rehabilitation: Assistive Technology 12, no. 5 (2016): 491–503. http://dx.doi.org/10.3109/17483107.2016.1151954.
Full text
24
Sajda, Paul, Andrew Laine, and Yehoshua Zeevi. "Multi-Resolution and Wavelet Representations for Identifying Signatures of Disease." Disease Markers 18, no. 5-6 (2002): 339–63. http://dx.doi.org/10.1155/2002/108741.
Full textAbstract:
Identifying physiological and anatomical signatures of disease in signals and images is one of the fundamental challenges in biomedical engineering. The challenge is most apparent given that such signatures must be identified in spite of tremendous inter and intra-subject variability and noise. Crucial for uncovering these signatures has been the development of methods that exploit general statistical properties of natural signals. The signal processing and applied mathematics communities have developed, in recent years, signal representations which take advantage of Gabor-type and wavelet-type functions that localize signal energy in a joint time-frequency and/or space-frequency domain. These techniques can be expressed as multi-resolution transformations, of which perhaps the best known is the wavelet transform. In this paper we review wavelets, and other related multi-resolution transforms, within the context of identifying signatures for disease. These transforms construct a general representation of signals which can be used in detection, diagnosis and treatment monitoring. We present several examples where these transforms are applied to biomedical signal and imaging processing. These include computer-aided diagnosis in mammography, real-time mosaicking of ophthalmic slit-lamp imagery, characterization of heart disease via ultrasound, predicting epileptic seizures and signature analysis of the electroencephalogram, and reconstruction of positron emission tomography data.
25
Lawford, Patricia V., Andrew V. Narracott, Keith McCormack, et al. "Virtual physiological human: training challenges." Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences 368, no. 1921 (2010): 2841–51. http://dx.doi.org/10.1098/rsta.2010.0082.
Full textAbstract:
The virtual physiological human (VPH) initiative encompasses a wide range of activities, including structural and functional imaging, data mining, knowledge discovery tool and database development, biomedical modelling, simulation and visualization. The VPH community is developing from a multitude of relatively focused, but disparate, research endeavours into an integrated effort to bring together, develop and translate emerging technologies for application, from academia to industry and medicine. This process initially builds on the evolution of multi-disciplinary interactions and abilities, but addressing the challenges associated with the implementation of the VPH will require, in the very near future, a translation of quantitative changes into a new quality of highly trained multi-disciplinary personnel. Current strategies for undergraduate and on-the-job training may soon prove insufficient for this. The European Commission seventh framework VPH network of excellence is exploring this emerging need, and is developing a framework of novel training initiatives to address the predicted shortfall in suitably skilled VPH-aware professionals. This paper reports first steps in the implementation of a coherent VPH training portfolio.
26
Viceconti, Marco. "A tentative taxonomy for predictive models in relation to their falsifiability." Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences 369, no. 1954 (2011): 4149–61. http://dx.doi.org/10.1098/rsta.2011.0227.
Full textAbstract:
The growing importance of predictive models in biomedical research raises some concerns on the correct methodological approach to the falsification of such models, as they are developed in interdisciplinary research contexts between physics, biology and medicine. In each of these research sectors, there are established methods to develop cause–effect explanations for observed phenomena, which can be used to predict: epidemiological models, biochemical models, biophysical models, Bayesian models, neural networks, etc. Each research sector has accepted processes to verify how correct these models are (falsification). But interdisciplinary research imposes a broader perspective, which encompasses all possible models in a general methodological framework of falsification. The present paper proposes a general definition of ‘scientific model’ that makes it possible to categorize predictive models into broad categories. For each of these categories, generic falsification strategies are proposed, except for the so-called ‘abductive’ models. For this category, which includes artificial neural networks, Bayesian models and integrative models, the definition of a generic falsification strategy requires further investigation by researchers and philosophers of science.
27
Charbon, E. "Single-photon imaging in complementary metal oxide semiconductor processes." Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences 372, no. 2012 (2014): 20130100. http://dx.doi.org/10.1098/rsta.2013.0100.
Full textAbstract:
This paper describes the basics of single-photon counting in complementary metal oxide semiconductors, through single-photon avalanche diodes (SPADs), and the making of miniaturized pixels with photon-counting capability based on SPADs. Some applications, which may take advantage of SPAD image sensors, are outlined, such as fluorescence-based microscopy, three-dimensional time-of-flight imaging and biomedical imaging, to name just a few. The paper focuses on architectures that are best suited to those applications and the trade-offs they generate. In this context, architectures are described that efficiently collect the output of single pixels when designed in large arrays. Off-chip readout circuit requirements are described for a variety of applications in physics, medicine and the life sciences. Owing to the dynamic nature of SPADs, designs featuring a large number of SPADs require careful analysis of the target application for an optimal use of silicon real estate and of limited readout bandwidth. The paper also describes the main trade-offs involved in architecting such chips and the solutions adopted with focus on scalability and miniaturization.
28
Kipli, Kuryati, Mohammed Enamul Hoque, Lik Thai Lim, et al. "A Review on the Extraction of Quantitative Retinal Microvascular Image Feature." Computational and Mathematical Methods in Medicine 2018 (July 2, 2018): 1–21. http://dx.doi.org/10.1155/2018/4019538.
Full textAbstract:
Digital image processing is one of the most widely used computer vision technologies in biomedical engineering. In the present modern ophthalmological practice, biomarkers analysis through digital fundus image processing analysis greatly contributes to vision science. This further facilitates developments in medical imaging, enabling this robust technology to attain extensive scopes in biomedical engineering platform. Various diagnostic techniques are used to analyze retinal microvasculature image to enable geometric features measurements such as vessel tortuosity, branching angles, branching coefficient, vessel diameter, and fractal dimension. These extracted markers or characterized fundus digital image features provide insights and relates quantitative retinal vascular topography abnormalities to various pathologies such as diabetic retinopathy, macular degeneration, hypertensive retinopathy, transient ischemic attack, neovascular glaucoma, and cardiovascular diseases. Apart from that, this noninvasive research tool is automated, allowing it to be used in large-scale screening programs, and all are described in this present review paper. This paper will also review recent research on the image processing-based extraction techniques of the quantitative retinal microvascular feature. It mainly focuses on features associated with the early symptom of transient ischemic attack or sharp stroke.
29
Kim, Junho, and Mucheol Kim. "DeepBlockShield: Blockchain Agent-Based Secured Clinical Data Management Model from the Deep Web Environment." Mathematics 9, no. 9 (2021): 1069. http://dx.doi.org/10.3390/math9091069.
Full textAbstract:
With the growth of artificial intelligence in healthcare and biomedical research, many researchers are interested in large amounts of data in hospitals and medical research centers. Then the need for remote medicine services and clinical data utilization are expanding. However, since the misuse and abuse of clinical data causes serious problems, the scope of its use is bound to have a limited range physically and logically. Then a security-enhanced data distribution system for medical deep web environments. Therefore, in this paper, we propose a blockchain-based clinical data management model named DeepBlockshield to prevent information leakage between the deep web and the surface web. Blockchain supports data integrity and user validation to support data sharing in closed networks. Meanwhile, the agent performs integrity verification between the blockchain and the deep web and strengthens the security between the surface web and the deep web. DeepBlockShield verifies the user’s validity through the records of the deep web and blockchain. Furthermore, we wrap the results analyzed by the valid request into a web interface and provide information to the requester asynchronously. In the experiment, the block generation cycle and size on the delay time was analyzed for verifying the stability of the blockchain network. As a result, it showed that the proposed approach guarantees the integrity and availability of clinical data in the deep web environment.
30
Brewster, John F., M. Ruth Graham, and W. Alan C. Mutch. "Convexity, Jensen's inequality and benefits of noisy mechanical ventilation." Journal of The Royal Society Interface 2, no. 4 (2005): 393–96. http://dx.doi.org/10.1098/rsif.2005.0043.
Full textAbstract:
Mechanical ventilators breathe for you when you cannot or when your lungs are too sick to do their job. Most ventilators monotonously deliver the same-sized breaths, like clockwork; however, healthy people do not breathe this way. This has led to the development of a biologically variable ventilator—one that incorporates noise. There are indications that such a noisy ventilator may be beneficial for patients with very sick lungs. In this paper we use a probabilistic argument, based on Jensen's inequality, to identify the circumstances in which the addition of noise may be beneficial and, equally important, the circumstances in which it may not be beneficial. Using the local convexity of the relationship between airway pressure and tidal volume in the lung, we show that the addition of noise at low volume or low pressure results in higher mean volume (at the same mean pressure) or lower mean pressure (at the same mean volume). The consequence is enhanced gas exchange or less stress on the lungs, both clinically desirable. The argument has implications for other life support devices, such as cardiopulmonary bypass pumps. This paper illustrates the benefits of research that takes place at the interface between mathematics and medicine.
31
Zulkri, Muhammad Farezuan, Shazlyn Milleana Shaharudin, Noor Azrin Abdul Rajak, and Muhammad Safwan Ibrahim. "Predictive Analytics on Academic Performance in Higher Education Institution during COVID-19 using Regression Model." International Journal of Biology and Biomedical Engineering 15 (May 25, 2021): 184–89. http://dx.doi.org/10.46300/91011.2021.15.21.
Full textAbstract:
The coronavirus disease 2019 (COVID-19) outbreak in December 2019 had affected the way of living for people around the world including students in educational institutions. These students had to prepare for the continuity of their study mentally and physically by adapting to the online teaching and learning approach, which can significantly impact their academic performance. Hence, this study examines the students' academic performance on the online teaching and learning approach, thus predicting their academic performance for the upcoming semester. This study enables various actions to be taken in improving and maintaining the student's performance in their study activities. The study was conducted on undergraduate students from the Faculty of Science and Mathematics, Universiti Pendidikan Sultan Idris. This paper presents the prediction of the student's academic performance with a linear regression model. Evidently, the result shows that the student's academic performance continually improves while adapting to the online teaching and learning approach. It also shows that there were few respondents affected while adapting to this new norm approach. Hence, the future development of the regression model can be improved by having a more comprehensive range of Malaysian universities' data.
32
Vera, Julio, Christopher Lischer, Momchil Nenov, Svetoslav Nikolov, Xin Lai, and Martin Eberhardt. "Mathematical Modelling in Biomedicine: A Primer for the Curious and the Skeptic." International Journal of Molecular Sciences 22, no. 2 (2021): 547. http://dx.doi.org/10.3390/ijms22020547.
Full textAbstract:
In most disciplines of natural sciences and engineering, mathematical and computational modelling are mainstay methods which are usefulness beyond doubt. These disciplines would not have reached today’s level of sophistication without an intensive use of mathematical and computational models together with quantitative data. This approach has not been followed in much of molecular biology and biomedicine, however, where qualitative descriptions are accepted as a satisfactory replacement for mathematical rigor and the use of computational models is seen by many as a fringe practice rather than as a powerful scientific method. This position disregards mathematical thinking as having contributed key discoveries in biology for more than a century, e.g., in the connection between genes, inheritance, and evolution or in the mechanisms of enzymatic catalysis. Here, we discuss the role of computational modelling in the arsenal of modern scientific methods in biomedicine. We list frequent misconceptions about mathematical modelling found among biomedical experimentalists and suggest some good practices that can help bridge the cognitive gap between modelers and experimental researchers in biomedicine. This manuscript was written with two readers in mind. Firstly, it is intended for mathematical modelers with a background in physics, mathematics, or engineering who want to jump into biomedicine. We provide them with ideas to motivate the use of mathematical modelling when discussing with experimental partners. Secondly, this is a text for biomedical researchers intrigued with utilizing mathematical modelling to investigate the pathophysiology of human diseases to improve their diagnostics and treatment.
33
Vera, Julio, Christopher Lischer, Momchil Nenov, Svetoslav Nikolov, Xin Lai, and Martin Eberhardt. "Mathematical Modelling in Biomedicine: A Primer for the Curious and the Skeptic." International Journal of Molecular Sciences 22, no. 2 (2021): 547. http://dx.doi.org/10.3390/ijms22020547.
Full textAbstract:
In most disciplines of natural sciences and engineering, mathematical and computational modelling are mainstay methods which are usefulness beyond doubt. These disciplines would not have reached today’s level of sophistication without an intensive use of mathematical and computational models together with quantitative data. This approach has not been followed in much of molecular biology and biomedicine, however, where qualitative descriptions are accepted as a satisfactory replacement for mathematical rigor and the use of computational models is seen by many as a fringe practice rather than as a powerful scientific method. This position disregards mathematical thinking as having contributed key discoveries in biology for more than a century, e.g., in the connection between genes, inheritance, and evolution or in the mechanisms of enzymatic catalysis. Here, we discuss the role of computational modelling in the arsenal of modern scientific methods in biomedicine. We list frequent misconceptions about mathematical modelling found among biomedical experimentalists and suggest some good practices that can help bridge the cognitive gap between modelers and experimental researchers in biomedicine. This manuscript was written with two readers in mind. Firstly, it is intended for mathematical modelers with a background in physics, mathematics, or engineering who want to jump into biomedicine. We provide them with ideas to motivate the use of mathematical modelling when discussing with experimental partners. Secondly, this is a text for biomedical researchers intrigued with utilizing mathematical modelling to investigate the pathophysiology of human diseases to improve their diagnostics and treatment.
34
Codling, Edward A., Michael J. Plank, and Simon Benhamou. "Random walk models in biology." Journal of The Royal Society Interface 5, no. 25 (2008): 813–34. http://dx.doi.org/10.1098/rsif.2008.0014.
Full textAbstract:
Mathematical modelling of the movement of animals, micro-organisms and cells is of great relevance in the fields of biology, ecology and medicine. Movement models can take many different forms, but the most widely used are based on the extensions of simple random walk processes. In this review paper, our aim is twofold: to introduce the mathematics behind random walks in a straightforward manner and to explain how such models can be used to aid our understanding of biological processes. We introduce the mathematical theory behind the simple random walk and explain how this relates to Brownian motion and diffusive processes in general. We demonstrate how these simple models can be extended to include drift and waiting times or be used to calculate first passage times. We discuss biased random walks and show how hyperbolic models can be used to generate correlated random walks. We cover two main applications of the random walk model. Firstly, we review models and results relating to the movement, dispersal and population redistribution of animals and micro-organisms. This includes direct calculation of mean squared displacement, mean dispersal distance, tortuosity measures, as well as possible limitations of these model approaches. Secondly, oriented movement and chemotaxis models are reviewed. General hyperbolic models based on the linear transport equation are introduced and we show how a reinforced random walk can be used to model movement where the individual changes its environment. We discuss the applications of these models in the context of cell migration leading to blood vessel growth (angiogenesis). Finally, we discuss how the various random walk models and approaches are related and the connections that underpin many of the key processes involved.
35
Burg, Timothy, Cheryl A. P. Cass, Richard Groff, Matthew Pepper, and Karen J. L. Burg. "Building off-the-shelf tissue-engineered composites." Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences 368, no. 1917 (2010): 1839–62. http://dx.doi.org/10.1098/rsta.2010.0002.
Full textAbstract:
Rapid advances in technology have created the realistic possibility of personalized medicine. In 2000, Time magazine listed tissue engineering as one of the ‘hottest 10 career choices’. However, in the past decade, only a handful of tissue-engineered products were translated to the clinical market and none were financially viable. The reality of complex business planning and the high-investment, high-technology environment was not apparent, and the promise of tissue engineering was overstated. In the meantime, biologists were steadily applying three-dimensional benchtop tissue-culture systems for cellular research, but the systems were gelatinous and thus limited in their ability to facilitate the development of complex tissues. Now, the bioengineering literature has seen an emergence of literature describing biofabrication of tissues and organs. However, if one looks closely, again, the viable products appear distant. ‘Rapid’ prototyping to reproduce the intricate patterns of whole organs using large volumes of cellular components faces daunting challenges. Homogenous forms are being labelled ‘tissues’, but, in fact, do not represent the heterogeneous structure of the native biological system. In 2003, we disclosed the concept of combining rapid prototyping techniques with tissue engineering technologies to facilitate precision development of heterogeneous complex tissue-test systems, i.e. systems to be used for drug discovery and the study of cellular behaviour, biomedical devices and progression of disease. The focus of this paper is on the challenges we have faced since that time, moving this concept towards reality, using the case of breast tissue as an example.
36
Jha, Balanand, Kumar Abhishek, Akshay Deepak, Shubhnkar Upadhyay, and Avadhesh Singh. "Ontology Based Clinical Decision Support System for Geriatrics." Journal of Computational and Theoretical Nanoscience 17, no. 1 (2020): 267–72. http://dx.doi.org/10.1166/jctn.2020.8661.
Full textAbstract:
This paper discusses an ontology based clinical decision support system for the specialty of Geriatric Medicine. We created a domain level ontology based on Handbook of Geriatrics and then mapped it to an upper level Basic Formal Ontology. The decision support system has been developed in Prolog. For accessing this ontology, we created an interactive web and android application which acts as a front-end to the system. Both applications are able to display the ontology structure and to predict the disease based on the symptom entered. We have uploaded our ontology to Bio-Portal, which is one of the most comprehensive biomedical ontology repository. It can be accessed using the URL https://bioportal.bioontology.org/ontologies/G-O.
37
Townsend-Nicholson, Andrea. "Educating and engaging new communities of practice with high performance computing through the integration of teaching and research." Interface Focus 10, no. 6 (2020): 20200003. http://dx.doi.org/10.1098/rsfs.2020.0003.
Full textAbstract:
The identification of strategies by which to increase the representation of women and increase diversity in STEM fields (science, technology, engineering and mathematics), including medicine, has been a pressing matter for global agencies including the European Commission, UNESCO and numerous international scientific societies. In my role as UCL training lead for CompBioMed, a European Commission Horizon 2020-funded Centre of Excellence in Computational Biomedicine (compbiomed.eu), and as Head of Teaching for Molecular Biosciences at UCL from 2010 to 2019, I have integrated research and teaching to lead the development of high-performance computing (HPC)-based education targeting medical students and undergraduate students studying biosciences in a way that is explicitly integrated into the existing university curriculum as a credit-bearing module. One version of the credit-bearing module has been specifically designed for medical students in their pre-clinical years of study and one of the unique features of the course is the integration of clinical and computational aspects, with students obtaining and processing clinical samples and then interrogating the results computationally using code that was ported to HPC at CompBioMed's HPC Facility core partners (EPCC (UK), SURFsara (The Netherlands) and the Barcelona Supercomputing Centre (Spain)). Another version of the credit-bearing module has, over the course of this project, evolved into a replacement for the third year research project course for undergraduate biochemistry, biotechnology and molecular biology students, providing students with the opportunity to design and complete an entire specialist research project from the formulation of experimental hypotheses to the investigation of these hypotheses in a way that involves the integration of experimental and HPC-based computational methodologies. Since 2017–2018, these UCL modules have been successfully delivered to over 350 students—a cohort with a demographic of greater than 50% female. CompBioMed's experience with these two university modules has enabled us to distil our methodology into an educational template that can be delivered at other universities in Europe and worldwide. This educational approach to training enables new communities of practice to effectively engage with HPC and reveals a means by which to improve the underrepresentation of women in supercomputing.
38
Ma, Pengcheng, and Qian Gao. "EEG Signal and Feature Interaction Modeling-Based Eye Behavior Prediction Research." Computational and Mathematical Methods in Medicine 2020 (May 16, 2020): 1–10. http://dx.doi.org/10.1155/2020/2801015.
Full textAbstract:
In recent years, with the development of brain science and biomedical engineering, as well as the rapid development of electroencephalogram (EEG) signal analysis methods, using EEG signals to monitor human health has become a very popular research field. The innovation of this paper is to analyze the EEG signal for the first time by building a depth factorization machine model, so that on the basis of analyzing the characteristics of user interaction, we can use EEG data to predict the binomial state of eyes (open eyes and closed eyes). The significance of the research is that we can diagnose the fatigue and the health of the human body by detecting the state of eyes for a long time. On the basis of this inference, the proposed method can make a further useful auxiliary support for improving the accuracy of the recommendation system recommendation results. In this paper, we first extract the features of EEG data by wavelet transform technology and then build a depth factorization machine model (FM+LSTM) which combines factorization machine (FM) and Long Short-Term Memory (LSTM) in parallel. Through the test of real data set, the proposed model gets more efficient prediction results than other classifier models. In addition, the model proposed in this paper is suitable not only for the determination of eye features but also for the acquisition of interactive features (user fatigue) in the recommendation system. The conclusion obtained in this paper will be an important factor in the determination of user preferences in the recommendation system, which will be used in the analysis of interactive features by the graph neural network in the future work.
39
"Biomedical research methodology based on GH-Method: math-physical medicine (No. 310)." Journal of Applied Material Science & Engineering Research 4, no. 3 (2020). http://dx.doi.org/10.33140/jamser.04.03.05.
Full textAbstract:
This paper discusses the author’s biomedical research work based on the GH-Method: math-physical medicine (MPM) approach over the past decade. This is significantly different from the traditional medical research using biochemical approach and simple statistical methods. He uses his own type 2 diabetes (T2D) metabolic conditions as a case study including several application examples as illustrations and explanations of the MPM methodology. The MPM methodology will be described, then followed by 10 application examples to show how he applied his knowledge and disciplines in mathematics, physics, engineering modeling, computer science tools, and psychology during his 10-years of biomedical research, especially in the domain of lifestyle, metabolism, chronic diseases, diabetes, cardiovascular diseases, and renal complications. The following list highlights the math-physical concepts, theories, principles, or equations used in the 10 application examples: 1. Topology, finite element method 2. Time-domain analysis, correlation and regression model, pattern recognition, segmentation analysis 3. Signal processing, trial and error method, regression analysis 4. Artificial intelligence (AI) auto-correction, quantum mechanics, safety margin of engineering design 5. Optical physics, AI, perturbation theory of quantum mechanics 6. Wave theory, Fourier transform, frequency-domain analysis 7. Structural engineering modeling, solid mechanics (both elastic and plastic), fluids dynamics, energy theory 8. Pattern recognition, behavior psychology 9. Spatial analysis, time-series analysis 10. Big data analytics, AI, software engineering Using MPM, a non-traditional medical research methodology, provides many quantitative proofs with a high degree of accuracy (higher precision) compared to other disease research results. Medicine is based on biology and chemistry, while biology, chemistry, and engineering are based on physics, and physics is based on mathematics. Logically, mathematics is the mother of all sciences. When we explore our application problems down to the foundation level, we can discover more facts and deeper truths. This is the logical essence of “math-physical medicine.” Using this MPM model, the accuracy of medical evaluations, along with the precision of predictive models can be greatly improved, with dramatic benefits to the patients.
40
Daldrup-Link, Heike E., Giuseppe Esposito, and Zaver M. Bhujwalla. "Challenges and Initiatives in Diversity, Equity and Inclusion in Cancer Molecular Imaging." Frontiers in Oncology 11 (April 9, 2021). http://dx.doi.org/10.3389/fonc.2021.638692.
Full textAbstract:
A diverse biomedical workforce is essential to achieve excellence in patient care, clinical translational, and basic research. Diversity, equity, and inclusion challenges in cancer molecular represent a combination of the challenges facing the science, technology, engineering, and mathematics (STEM) field, and challenges in Radiology and Nuclear Medicine. Although there is a growing awareness of conscious and unconscious bias that negatively affect the cancer imaging world, many challenges remain such as overcoming barriers to entry into the pipeline, avoiding program dropout, and providing long-term career prospect. The COVID-19 pandemic has resulted in a significant setback and further highlighted problems faced by women and underrepresented minorities. In this perspective, we have identified some of the challenges faced and highlighted ongoing and future initiatives to address these challenges.
41
Alber, Mark, Adrian Buganza Tepole, William R. Cannon, et al. "Integrating machine learning and multiscale modeling—perspectives, challenges, and opportunities in the biological, biomedical, and behavioral sciences." npj Digital Medicine 2, no. 1 (2019). http://dx.doi.org/10.1038/s41746-019-0193-y.
Full textAbstract:
AbstractFueled by breakthrough technology developments, the biological, biomedical, and behavioral sciences are now collecting more data than ever before. There is a critical need for time- and cost-efficient strategies to analyze and interpret these data to advance human health. The recent rise of machine learning as a powerful technique to integrate multimodality, multifidelity data, and reveal correlations between intertwined phenomena presents a special opportunity in this regard. However, machine learning alone ignores the fundamental laws of physics and can result in ill-posed problems or non-physical solutions. Multiscale modeling is a successful strategy to integrate multiscale, multiphysics data and uncover mechanisms that explain the emergence of function. However, multiscale modeling alone often fails to efficiently combine large datasets from different sources and different levels of resolution. Here we demonstrate that machine learning and multiscale modeling can naturally complement each other to create robust predictive models that integrate the underlying physics to manage ill-posed problems and explore massive design spaces. We review the current literature, highlight applications and opportunities, address open questions, and discuss potential challenges and limitations in four overarching topical areas: ordinary differential equations, partial differential equations, data-driven approaches, and theory-driven approaches. Towards these goals, we leverage expertise in applied mathematics, computer science, computational biology, biophysics, biomechanics, engineering mechanics, experimentation, and medicine. Our multidisciplinary perspective suggests that integrating machine learning and multiscale modeling can provide new insights into disease mechanisms, help identify new targets and treatment strategies, and inform decision making for the benefit of human health.
42
Storti, D. "Smooth Anatomical Models From 3D Imaging." Journal of Medical Devices 3, no. 2 (2009). http://dx.doi.org/10.1115/1.3135152.
Full textAbstract:
3D imaging has become a standard tool in medical diagnostics and, while software is available to visualize volumetric data sets, we do not yet have software that can efficiently transform 3D scan data to solid models that are useful for engineering design and analysis. Why not? Currently, deriving solid models from 3D scans involves 3 steps: (1) segmentation: identification of voxels associated with the structure; (2) polygonization: computing a set of polygons that approximate the surface of the structure; and (3) repair: removing stray voxels and polygons, specifying connectivity, and establishing consistent orientation. Significant progress has been made on accurate, automated segmentation (recent work by Hu et al. (Image Segmentation and Registration for the Analysis of Joint Motion From 3D MRI,” Proc SPIE 6141, pp. 133–142, Medical Imaging: Visualization, Image-Guided Procedures, & Display, 2006), combining graph cuts with level sets is of particular interest) but effective polygonization cannot be guaranteed. In the worst case, manual repairs are needed to patch holes and remove stray elements. Even if a valid boundary representation (b-rep) model is obtained, accurate models contain so many polygons that modeling operations become unfeasible. Moreover, regardless of accuracy, the surface of a polyhedral model will never be truly smooth. In previous work (Storti, D., et al., Artifact vs. Anatomy: Dealing With Conflict of Geometric Modeling Descriptions,” SAE 2007 Transactions Journal of Passenger Cars: Electronic and Electrical Systems, Paper No. 2007-01-2450, Vol. 116, pp. 813–823, 2007), we proposed overcoming the barriers to creating solid models from 3D scans by employing a new solid modeling description, wavelet SDF-reps, that lies much closer to the native 3D scan format and eliminates polygonization. Here, we focus on the ability to produce models with smooth surfaces that are important for various biomedical simulations. For example, careful studies of joint function involve detailed modeling of ligament wrapping; i.e., connective tissue moving across bone surface as the joint configuration changes. Realistic behavior cannot be obtained if the ligament is snagging on or snapping across convex vertices of a polyhedral model. Similarly, haptic simulation of a catheter navigating through the circulatory system cannot be realistic if the catheter gets stuck in concave vertices of the anatomical model. How can the new modeling format address such issues? Wavelet SDF-reps take advantage of a by-product of the segmentation algorithm (Hue et al.) which converts the raw voxel intensity values to a grid of signed distance values. Applying an appropriate interpolant such as Daubechies wavelets (Daubechies, I., Wavelets, CBMS-NS Series in Applied Mathematics, SIAM Publications, Philadelphia, 1992) then produces an implicit or function-based (f-rep) solid model of the segmented structure. Wavelet SDF-reps are inherently multi-resolution and support significant data compression and medial axis computation. We illustrate the capability of wavelet SDF-reps to support smooth models and enable analysis of curvature features.
43
"A standardized educational system for radiology programs worldwide: An opinion." Open Journal of Radiology and Medical Imaging, September 22, 2021, 53–54. http://dx.doi.org/10.36811/ojrmi.2021.110018.
Full textAbstract:
The educational system in radiology programs worldwide is different. In the American system, they offer a certificate program (Cert) then an associate degree (AAS) in some colleges then a diploma (Dip) after that a bachelor’s degree (B.S.). A radiographer a.k.a radiologic technologist can continue to get a post-baccalaureate certificate or a master’s degree (M.S.) and rarely in America due to the shortage of Ph.D. programs a doctorate of philosophy in radiology. The British system in radiology programs is more advanced than the American system which offers a bachelor’s degree (B.Sc.) then a post graduate certificate (PGCert) or post graduate diploma (PGDip) or a master’s degree (M.Sc.) and eventually a Ph.D. There are other countries with different educational systems in radiology which can vary from the previous two examples. All of these system does not standardize a one educational system that can work for everyone. The aim of this paper is to propose an educational system that is easy and effective. First of all, standardize the name of all the radiology programs. Radiology is a good name which will prevent confusion with other fields. For example, radiation science can be confused with physics. Medical imaging is a broad name that include any imaging as a picture of human skin with pathology or a picture of a microscopic slide of a human specimen can be included in medical imaging. Radiologic technology or biomedical imaging is confused with IT and engineering. Radiology is a perfect name that no one will be confused with. When someone says biology no one will think it means mathematics. Second, no degrees below bachelor degree except high school−level a.k.a a secondary education. The admission requirement is general educational diploma or high school certificate. The bachelor degree in radiology must be a 4-year long program that teaches all of the modalities (i.e., X-ray, Fluoroscopy, Computed Tomography (CT), Magnetic Resonance Imaging (MRI), Nuclear Medicine (NM), Ultrasound (US), Doppler, Catheterization lab and Angiography, etc.). This will prevent the track system which makes issues in the work market by over saturating one track. Third, a master’s degree in radiology that offer a sub-specialty in one modality. Like a master’s degree in CT alone, ultrasound alone, radiation protection alone, or Picture Archiving and Communication system (PACs) alone. The master’s program can be 1 or 2 years. Fourth, the Ph.D. program should focus on one system of the human body or a category of imaging like: PhD in neuroimaging, gynecology and obstetrics ultrasound, forensic imaging, pediatric imaging, or cardiovascular imaging, etc. The PhD program is more subspecialized program in a very small area. The Ph.D. program can be from 3 to 5 years long. This is a very simple system and applicable which will allow more consistence in the radiology educational systems worldwide.
44
"Abstracts from the 6th Australian Conference on Mathematics and Computers in Sport, 1-3 July 2002, Bond University, Queensland, Australia." Sports Engineering 5, no. 4 (2002): 239–44. http://dx.doi.org/10.1046/j.1460-2687.2002.00114.x.
Full text
45
"Editorial." Journal of The Royal Society Interface 1, no. 1 (2004): 1. http://dx.doi.org/10.1098/rsif.2004.0015.
Full textAbstract:
Through its peer-reviewed scientific publications, The Royal Society has been benchmarking original scientific research at the highest international level for many years. Hitherto, the record has been conveniently and neatly divided into publications devoted either to the physical sciences, including mathematics, or to the biological sciences. However, in recent times, it has been apparent that distinctive scientific challenges and opportunities exist at the interface between the major scientific monoliths. As a consequence, interdisciplinary, multidisciplinary and cross-disciplinary research is flourishing on a global scale as the methodologies of chemistry, computer science, materials science, mathematics and physics are employed to provide insight into the biological and medical sciences. Equally, a greater understanding of the biological template has considerable potential to facilitate advances in the physical sciences. Consequently it is appropriate, and timely, to launch Journal of the Royal Society Interface , as a mechanism for publishing papers from the spectrum between the physical and life sciences. Articles are welcomed on topics including biocomplexity, bioengineering, bioinformatics, biomaterials, biomechanics, biophysics, chemical biology, medical physics, systems biology, theoretical biology and tissue engineering. Within this diverse range of topics, my personal experience is as a materials scientist who developed an early interest in the deformation and fracture of bone using microstrain-measuring techniques and associated fracture-mechanics analysis, but with an associated need to understand bone biology. From this base developed radical research on bone analogues, i.e. novel materials to replace or repair bone, based on the control of cell attachment, proliferation and extracellular matrix production on surfaces of appropriate chemistry, topography and mechanical property. Such cross-disciplinary research requires expertise in cell biology, biochemistry, materials science, mechanics and medical science, and it has culminated in current approaches to biomaterials and tissue engineering, which have the potential to change radically the prospects for regenerative medicine. This cross-disciplinary approach resonates across the spectrum of potential topics for the journal, with the expectation that combinations of scientific insights will be a common factor. As Editor, I have the ambition that Journal of the Royal Society Interface will empower the advance of cross-disciplinary science. I recognise that our success will depend on the quality and impact of the submitted papers we publish; to this end, we shall continue the exemplary standards of peer review and rapid publication established by the other Royal Society journals. Hence, with my colleagues on the Editorial Board, I welcome the submission of articles, reports and reviews which contribute to the advancement of knowledge within the interface theme of the journal. This first hardcopy issue incorporates the papers that we have already published online. We shall continue to publish papers individually following acceptance so as to achieve prompt dissemination to the community, with collected papers made up into issues of this scale.
46
Harrison, James H., John R. Gilbertson, Matthew G. Hanna, et al. "Introduction to Artificial Intelligence and Machine Learning for Pathology." Archives of Pathology & Laboratory Medicine, January 22, 2021. http://dx.doi.org/10.5858/arpa.2020-0541-cp.
Full textAbstract:
Context.— Recent developments in machine learning have stimulated intense interest in software that may augment or replace human experts. Machine learning may impact pathology practice by offering new capabilities in analysis, interpretation, and outcomes prediction using images and other data. The principles of operation and management of machine learning systems are unfamiliar to pathologists, who anticipate a need for additional education to be effective as expert users and managers of the new tools. Objective.— To provide a background on machine learning for practicing pathologists, including an overview of algorithms, model development, and performance evaluation; to examine the current status of machine learning in pathology and consider possible roles and requirements for pathologists in local deployment and management of machine learning systems; and to highlight existing challenges and gaps in deployment methodology and regulation. Data Sources.— Sources include the biomedical and engineering literature, white papers from professional organizations, government reports, electronic resources, and authors' experience in machine learning. References were chosen when possible for accessibility to practicing pathologists without specialized training in mathematics, statistics, or software development. Conclusions.— Machine learning offers an array of techniques that in recent published results show substantial promise. Data suggest that human experts working with machine learning tools outperform humans or machines separately, but the optimal form for this combination in pathology has not been established. Significant questions related to the generalizability of machine learning systems, local site verification, and performance monitoring remain to be resolved before a consensus on best practices and a regulatory environment can be established.