Relevant bibliographies by topics / Therapeutic algorithms

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Therapeutic algorithms'

Author: Grafiati
Published: 7 June 2025
Last updated: 26 June 2025

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Journal articles on the topic "Therapeutic algorithms"

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Rusli, Rusli, Nurisyah Nurisyah, Sisilia Teresia Rosmala Dewi, et al. "Towards optimal diabetes therapy management: An evaluation of therapy algorithms for type 2 diabetes mellitus at community health centers (CHCs) in Makassar City, South Sula-wesi, Indonesia." Pharmacia 72 (February 27, 2025): 1–7. https://doi.org/10.3897/pharmacia.72.e139314.

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The proper use of medications in managing diabetes mellitus (DM) is essential for achieving the best therapeutic results. Assessing the alignment of drug prescriptions with therapeutic algorithms plays a vital role in ensuring effective treatment for DM patients. This study aims to evaluate the appropriateness of medication use in DM patients according to therapeutic algorithms at community health centers (CHCs) in Makassar City, Indonesia. A cross-sectional study was conducted at five CHCs, involving 299 DM patients, including 108 males and 191 females. Data on demographics (gender, age, education, and occupation) and medication use were collected. The rationality of drug use was evaluated based on indication, drug choice, dosage, and patient suitability. Biguanides, especially metformin, were the most frequently used drugs (60.3%), followed by sulfonylureas (29%) and insulin (10.7%). The overall appropriateness of medication use according to therapeutic algorithms was 86%. However, there were shortcomings in terms of correct dosage, where approximately 30.10% of patients still received inappropriate doses. Most DM patients at the studied CHCs received medications aligned with therapeutic guidelines, demonstrating a high level of conformity in prescribing practices.
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Wei, Wei, Liang Liu, Zhong Qin Hu, and Yu Jing Zhou. "Rigid Medical Image Registration Based on Genetic Algorithms and Mutual Information." Applied Mechanics and Materials 665 (October 2014): 712–17. http://dx.doi.org/10.4028/www.scientific.net/amm.665.712.

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With the variety of medical imaging equipment’s application in the medical process,medical image registration becomes particularly important in the field of medical image processing,which has important clinical diagnostic and therapeutic value. This article describes the matrix conversion method of the rigid registration model, the basic concepts and principles of the mutual information algorithm ,the basic idea of genetic algorithms and algorithm’s flow , and the application of the improved genetic algorithms in practice. The rigid registration of two CT brain bones images uses mutual information as a similarity measure, genetic algorithm as the search strategy and matlab as programming environment. Using the three-point crossover technique to exchange the three parameters in the rigid transformation repeectively to produce new individuals, the genetic algorithm’s local search ability enhanced and the prematurity phenomenon can be reduced through the depth study of the basic genetic algorithm. The experiments show that the registration has high stability and accuracy.
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Rodríguez-Padilla, Á. "Diagnostic and therapeutic algorithms for hepatobiliar surgery." ACTUALIDAD MEDICA 103, no. 804 (2018): 104. http://dx.doi.org/10.15568/am.2018.804.cl01.

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Jalilovna, Khalimova Dilrabo. "Acute back pain: Diagnostic and therapeutic algorithms." ACADEMICIA: AN INTERNATIONAL MULTIDISCIPLINARY RESEARCH JOURNAL 11, no. 1 (2021): 316–20. http://dx.doi.org/10.5958/2249-7137.2021.00045.8.

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Roith, Derek Le. "Current therapeutic algorithms for type 2 diabetes." Clinical Cornerstone 4, no. 2 (2001): 38–49. http://dx.doi.org/10.1016/s1098-3597(01)90028-6.

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Salome, Geraldo Magela. "Content validity and internal consistency of an algorithm for cleansing wounds with granulation and necrotic tissues." Saúde (Santa Maria) 50, no. 1 (2024): 1–17. http://dx.doi.org/10.5902/2236583484498.

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Protocols in the form of algorithms allow the nurse team to make rapid decisions, lowering risks and improving outcome. There is a lack of readily available protocols for the use of correct techniques and products for wound cleansing. Objective. To assess the content validity and internal consistency of an algorithm for cleansing wounds with granulation and necrotic tissues. Methods. A literature search was conducted to identify relevant studies for the construction of the algorithm, using the following descriptors: “wounds and injuries”, “algorithms”, “cleansing agents”, “therapeutic irrigation”, and “debridement” in both English, Brazilian Portuguese and Spanish. The development of the algorithm involved the planning and production of content and definition of topics. The algorithm was assessed for content validity by 20 judges and for internal consistency by 31 judges. Results. An algorithm was developed to help health professionals in the cleansing of wounds. It describes wound cleansing techniques and provides recommendations for therapeutic interventions and primary dressings, based on the type of wound tissue. The judges assessing the content validity of the algorithm reached consensus in two rounds of consultation. The algorithm showed good internal consistency with a Cronbach’s alpha of 0.851. Conclusions. The validated algorithms will provide health professionals with relevant information to choose appropriate wound cleansing techniques and therapeutic procedures according to the type of wound tissue.
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Mangues, M. Antonia, Joaquin Bonal, Rosa Farré, and J. Francesc Massó. "Algorithms for Dosage and Therapeutic Monitoring of Theophylline." Drug Intelligence & Clinical Pharmacy 22, no. 11 (1988): 893–94. http://dx.doi.org/10.1177/106002808802201114.

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Theophylline is widely prescribed in Spain. Because this drug has a narrow therapeutic range and high interindividual pharmacokinetic variability, it is essential to adapt the dosage to each patient. In order to simplify the drug individualization we are proposing three algorithms to apply to intravenous loading and maintenance doses and to oral doses. The initial recommended dosages have been established using the pharmacokinetic parameters obtained from patients treated with theophylline in our hospital. Because the pharmacokinetic behavior of theophylline may be different in other populations, dosage requirements may not be the same. A minimum number of blood sample collections is proposed in an attempt to improve the cost-benefit relationship in theophylline therapy.
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Parker, Andrew S., Wei Zheng, Karl E. Griswold, and Chris Bailey-Kellogg. "Optimization algorithms for functional deimmunization of therapeutic proteins." BMC Bioinformatics 11, no. 1 (2010): 180. http://dx.doi.org/10.1186/1471-2105-11-180.

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Swedberg, Karl. "Diagnostic and Therapeutic Algorithms in Chronic Heart Failure." Herz Kardiovaskuläre Erkrankungen 31, no. 9 (2006): 877–80. http://dx.doi.org/10.1007/s00059-006-2927-2.

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Perlstein, Todd S., Samuel Z. Goldhaber, Kerrie Nelson, et al. "The Creating an Optimal Warfarin Nomogram (CROWN) Study." Thrombosis and Haemostasis 107, no. 01 (2012): 59–68. http://dx.doi.org/10.1160/th11-08-0568.

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SummaryA significant proportion of warfarin dose variability is explained by variation in the genotypes of the cytochrome P450 CYP2C9 and the vitamin K epoxide reductase complex, VKORC1, enzymes that influence warfarin metabolism and sensitivity, respectively. We sought to develop an optimal pharmacogenetic warfarin dosing algorithm that incorporated clinical and genetic information. We enroled patients initiating warfarin therapy. Genotyping was performed of the VKORC1, –1639G>A, the CYP2C9*2, 430C>T, and the CYP2C9*3, 1075C>A genotypes. The initial warfarin dosing algorithm (Algorithm A) was based upon established clinical practice and published warfarin pharmacogenetic information. Subsequent dosing algorithms (Algorithms B and Algorithm C) were derived from pharmacokinetic / pharmacodynamic (PK/PD) modelling of warfarin dose, international normalised ratio (INR), clinical and genetic factors from patients treated by the preceding algorithm(s). The primary outcome was the time in the therapeutic range, considered an INR of 1.8 to 3.2. A total of 344 subjects are included in the study analyses. The mean percentage time within the therapeutic range for each subject increased progressively from Algorithm A to Algorithm C from 58.9 (22.0), to 59.7 (23.0), to 65.8 (16.9) percent (p = 0.04). Improvement also occurred in most secondary endpoints, which included the per-patient percentage of INRs outside of the therapeutic range (p = 0.004), the time to the first therapeutic INR (p = 0.07), and the time to achieve stable therapeutic anticoagulation (p < 0.001). In conclusion, warfarin pharmacogenetic dosing can be optimised in real time utilising observed PK/PD information in an adaptive fashion.Clinical Trial Registration: ClinicalTrials.gov (NCT00401414)
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Dissertations / Theses on the topic "Therapeutic algorithms"

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Tafas, Jihad. "An algorithm for two-dimensional density reconstruction in proton computed tomography (PCT)." CSUSB ScholarWorks, 2007. https://scholarworks.lib.csusb.edu/etd-project/3281.

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The purpose of this thesis is to develop an optimized and effective iterative reconstruction algorithm and hardware acceleration methods that work synonymously together through reconstruction in proton computed tomography, which accurately maps the electron density.
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Spadinger, Ingrid Teresa. "Algorithms for automated measurements of the radioresponse of live cells at therapeutic doses." Thesis, University of British Columbia, 1990. http://hdl.handle.net/2429/30851.

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The study of the effects of damaging agents on living cells is of importance both for the assessment of the potential consequences of exposure, and for the advancement of medical technologies concerned with the treatment of cancer and other diseases. Such agents, however, are commonly studied at doses and levels of effect much higher than those seen in environmental or even medical exposures. Studies of cell survival after treatment with ionizing radiation, for instance, generally involve the measurement of dose-response over several decades of cell kill on a logarithmic scale. In contrast, cell survival rates for a typical clinical treatment dose are on the order of 50%. Survival measurements in this first decade of cell kill require that the exact fate of thousands of cells is determined in a single experiment. This is beyond human capabilities. Measurements at these levels of effect therefore require the development of a rapid, automated system of cell detection, characterization, and follow-up. The primary aim of this thesis was to test the hypothesis that the algorithms necessary for generating survival data with such an automated system can be developed to standards of accuracy comparable to those of an experienced human observer. Using an image cytometry device specifically designed for the detection and analysis of live, unstained cells, automated scanning procedures were optimized for selected cell lines, and means of maintaining appropriate focus levels during a scan were devised. Algorithms to distinguish cells from other objects detected in the flask were also developed. These performed with comparable accuracy, but at greater speed, than could be achieved by a human observer. Because the endpoint used in survival measurements is the ability of treated cells to proliferate to form colonies, the hypothesis that automated methods of assaying colony formation could be developed was also tested. Using rapidly collected, low resolution image data obtained at locations in the tissue culture vessel where individual cells had been detected on the day of treatment, it was found that the survival status at 70-90% of these locations could be determined automatically. Manual assessments were required at the remaining locations. The final objective of this thesis was to use the methods developed for automated sample selection and survival assessment to examine a question relevant to both radiotherapeutic applications and the understanding of mechanisms of radiation action. In particular, the Theory of Dual Radiation Action (Kellerer and Rossi, 1972), which predicts that the relative biological effectiveness (RBE) of different modalities of sparsely ionizing radiations may change dramatically with decreasing dose, was tested experimentally. Using two different mammalian cell lines, the experimental data in general rejected the predictions of this theory, although a modified theory, developed by the same authors, could accommodate the results. In summary, the data showed that there may be a slight dose dependence in the RBE of the radiations tested. Specifically, the RBE of low energy X-rays relative to ⁶⁰Co γ-rays was found to increase slightly with decreasing dose. The measured RBE's in the zero-dose limit were ~1.4 for 55 kVp X-rays and ~1.1-1.2 for 250 kV[subscript]p X-rays. High energy (11 MeV) electrons, on the other hand, showed a small decrease in RBE relative to ⁶⁰Co γ-rays as the dose approached zero, having a zero-dose limit of ~0.95. All of the aforementioned radiation modalities had an RBE of 1.0-1.1 at high doses (10 Gy or more).<br>Science, Faculty of<br>Physics and Astronomy, Department of<br>Graduate
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Lian, Chunfeng. "Information fusion and decision-making using belief functions : application to therapeutic monitoring of cancer." Thesis, Compiègne, 2017. http://www.theses.fr/2017COMP2333/document.

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La radiothérapie est une des méthodes principales utilisée dans le traitement thérapeutique des tumeurs malignes. Pour améliorer son efficacité, deux problèmes essentiels doivent être soigneusement traités : la prédication fiable des résultats thérapeutiques et la segmentation précise des volumes tumoraux. La tomographie d’émission de positrons au traceur Fluoro- 18-déoxy-glucose (FDG-TEP) peut fournir de manière non invasive des informations significatives sur les activités fonctionnelles des cellules tumorales. Les objectifs de cette thèse sont de proposer: 1) des systèmes fiables pour prédire les résultats du traitement contre le cancer en utilisant principalement des caractéristiques extraites des images FDG-TEP; 2) des algorithmes automatiques pour la segmentation de tumeurs de manière précise en TEP et TEP-TDM. La théorie des fonctions de croyance est choisie dans notre étude pour modéliser et raisonner des connaissances incertaines et imprécises pour des images TEP qui sont bruitées et floues. Dans le cadre des fonctions de croyance, nous proposons une méthode de sélection de caractéristiques de manière parcimonieuse et une méthode d’apprentissage de métriques permettant de rendre les classes bien séparées dans l’espace caractéristique afin d’améliorer la précision de classification du classificateur EK-NN. Basées sur ces deux études théoriques, un système robuste de prédiction est proposé, dans lequel le problème d’apprentissage pour des données de petite taille et déséquilibrées est traité de manière efficace. Pour segmenter automatiquement les tumeurs en TEP, une méthode 3-D non supervisée basée sur le regroupement évidentiel (evidential clustering) et l’information spatiale est proposée. Cette méthode de segmentation mono-modalité est ensuite étendue à la co-segmentation dans des images TEP-TDM, en considérant que ces deux modalités distinctes contiennent des informations complémentaires pour améliorer la précision. Toutes les méthodes proposées ont été testées sur des données cliniques, montrant leurs meilleures performances par rapport aux méthodes de l’état de l’art<br>Radiation therapy is one of the most principal options used in the treatment of malignant tumors. To enhance its effectiveness, two critical issues should be carefully dealt with, i.e., reliably predicting therapy outcomes to adapt undergoing treatment planning for individual patients, and accurately segmenting tumor volumes to maximize radiation delivery in tumor tissues while minimize side effects in adjacent organs at risk. Positron emission tomography with radioactive tracer fluorine-18 fluorodeoxyglucose (FDG-PET) can noninvasively provide significant information of the functional activities of tumor cells. In this thesis, the goal of our study consists of two parts: 1) to propose reliable therapy outcome prediction system using primarily features extracted from FDG-PET images; 2) to propose automatic and accurate algorithms for tumor segmentation in PET and PET-CT images. The theory of belief functions is adopted in our study to model and reason with uncertain and imprecise knowledge quantified from noisy and blurring PET images. In the framework of belief functions, a sparse feature selection method and a low-rank metric learning method are proposed to improve the classification accuracy of the evidential K-nearest neighbor classifier learnt by high-dimensional data that contain unreliable features. Based on the above two theoretical studies, a robust prediction system is then proposed, in which the small-sized and imbalanced nature of clinical data is effectively tackled. To automatically delineate tumors in PET images, an unsupervised 3-D segmentation based on evidential clustering using the theory of belief functions and spatial information is proposed. This mono-modality segmentation method is then extended to co-segment tumor in PET-CT images, considering that these two distinct modalities contain complementary information to further improve the accuracy. All proposed methods have been performed on clinical data, giving better results comparing to the state of the art ones
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Dang, Vinh Q. "Evolutionary approaches for feature selection in biological data." Thesis, Edith Cowan University, Research Online, Perth, Western Australia, 2014. https://ro.ecu.edu.au/theses/1276.

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Data mining techniques have been used widely in many areas such as business, science, engineering and medicine. The techniques allow a vast amount of data to be explored in order to extract useful information from the data. One of the foci in the health area is finding interesting biomarkers from biomedical data. Mass throughput data generated from microarrays and mass spectrometry from biological samples are high dimensional and is small in sample size. Examples include DNA microarray datasets with up to 500,000 genes and mass spectrometry data with 300,000 m/z values. While the availability of such datasets can aid in the development of techniques/drugs to improve diagnosis and treatment of diseases, a major challenge involves its analysis to extract useful and meaningful information. The aims of this project are: 1) to investigate and develop feature selection algorithms that incorporate various evolutionary strategies, 2) using the developed algorithms to find the “most relevant” biomarkers contained in biological datasets and 3) and evaluate the goodness of extracted feature subsets for relevance (examined in terms of existing biomedical domain knowledge and from classification accuracy obtained using different classifiers). The project aims to generate good predictive models for classifying diseased samples from control.
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Melone, Marie-Anne. "Diagnοstic and therapeutic strategies οf circadian and sleep/wake rhythm disοrders in at-risk pοpulatiοns". Electronic Thesis or Diss., Normandie, 2024. http://www.theses.fr/2024NORMR023.

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Les recommandations en matière de santé du sommeil préconisent 7 à 9 heures de sommeil par nuit pour la population générale. Pourtant, la dette chronique de sommeil persiste et présente des risques importants pour la santé, notamment en termes de maladies métaboliques, cardiovasculaires et neurocognitives. Cette dette chronique de sommeil est souvent attribuée au conflit entre le mode de vie moderne - l'éclairage artificiel et les obligations sociales - et nos rythmes circadiens endogènes, ce qui conduit à une perturbation appelée le désalignement circadien. Les rythmes circadiens sont les oscillations naturelles des processus physiologiques. Ces rythmes sont essentiels pour aligner nos processus physiologiques et comportementaux sur le temps solaire afin d'anticiper les changements dans notre environnement. Le désalignement circadien est de plus en plus souvent incriminé dans divers états pathologiques. Le diagnostic des troubles des rythmes circadiens ou rythmes veille/sommeil reste difficile en pratique, car sa définition repose en partie sur des évaluations subjectives de la qualité du sommeil. Les questionnaires et les agendas de sommeil bien qu’ils soient des outils validés établissent des mesures indirectes de notre chronotype et des rythmes veille/sommeil. Le gold standard pour l’évaluation de notre rythmicité circadienne est la mesure biologique de la sécrétion de la mélatonine. Ceci souligne la nécessité d'améliorer les méthodes de diagnostic afin de mieux identifier la prévalence de ces troubles et ainsi pouvoir proposer des mesures thérapeutiques adaptée. Ceci pourrait contribuer à prévenir le développement de pathologies en liens avec ce désalignement circadien. Dans ce contexte, notre travail s’intéresse à la prévalence, les facteurs de risque et les conséquences des désalignements circadiens, chez des populations particulièrement à risque comme les étudiants-sportifs et les patients de soins intensifs, où les donneurs de temps sont perturbés ; générant des conséquences en termes d’altération des performances et du pronostic. Ce travail comprend les résultats de trois études et une revue de littérature sur la prévalence des troubles des rythmes veille/sommeil, leurs facteurs de risque, les conséquences et les traitements potentiels dans les populations des étudiants-sportifs et des patients de soins intensifs<br>Sleep health guidelines advocate for 7 to 9 hours of nightly sleep for the general population, yet sleep debt persists, presenting significant health risks, including metabolic, cardiac, mental, and neurocognitive diseases. This widespread sleep debt is often attributed to the conflict between modern lifestyles—characterized by artificial lighting, shift work, and social obligations—and our innate circadian rhythms, leading to a condition known as circadian dysrhythmia. Circadian rhythms are the natural oscillations in physiological processes that are essential for aligning genetic, physiological, and behavioral patterns with solar time to anticipate changes in our environment. The misalignment of these rhythms is increasingly linked to various health disorders. Diagnosing circadian rhythms and sleep/wake disorders poses challenges, as part of its definition relies on subjective assessments and clinical evaluations of sleep quality. Moreover, sleep/wake timing or chronotype questionnaires, although validated, may not accurately reflect individual circadian clocks. While melatonin measurement is considered the gold standard, its practical implementation is difficult, making actigraphy and sleep logs more common tools for identifying circadian rhythms and sleep/wake disorders. This highlights the need for improved diagnostic methods. Potential therapeutic interventions could help improve circadian dysrhythmias related health outcomes. In this context, this manuscript delves into the prevalence, risk factors, and consequences of circadian rhythms and sleep/wake disorders, particularly focusing on at-risk populations like student-athletes and critically ill patients, where misaligned zeitgebers exacerbate health risks. This work includes three studies’ findings and one narrative review on circadian rhythm and sleep/wake disorders, their risk factors, consequences, and potential treatments in populations prioritizing performance (student-athletes) and recovery (critically ill patients)
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Tiporlini, Valentina. "Magnetocardiography in unshielded environment based on optical magnetometry and adaptive noise cancellation." Thesis, Edith Cowan University, Research Online, Perth, Western Australia, 2013. https://ro.ecu.edu.au/theses/875.

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This thesis proposes and demonstrates the concept of a magnetocardiographic system employing an array of optically-pumped quantum magnetometers and an adaptive noise cancellation for heart magnetic field measurement within a magnetically-unshielded environment. Optically-pumped quantum magnetometers are based on the use of the atomic-spin-dependent optical properties of an atomic medium. An Mxconfiguration- based optically-pumped quantum magnetometer employing two sensing cells containing caesium vapour is theoretically described and experimentally developed, and the dependence of its sensitivity and frequency bandwidth upon the light power and the alkali vapour temperature is experimentally demonstrated. Furthermore, the capability of the developed magnetometer of measuring very weak magnetic fields is experimentally demonstrated in a magnetically-unshielded environment. The adaptive noise canceller is based on standard Least-Mean-Squares (LMS) algorithms and on two heuristic optimization techniques, namely, Genetic Algorithms (GA) and Particle Swarm Optimization (PSO). The use of these algorithms is investigated for suppressing the power line generated 50Hz interference and recovering of the weak magnetic heart signals from a much higher electromagnetic environmental noise. Experimental results show that all the algorithms can extract a weak heart signal from a much-stronger magnetic noise, detect the P, QRS, and T heart features and highly suppress the common power line noise component at 50 Hz. Moreover, adaptive noise cancellation based on heuristic algorithms is shown to be more efficient than adaptive noise canceller based on standard or normalised LMS algorithm in heart features detection.
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Wallace, Juanita Jean. "USING FOOT PRESSURE ANALYSIS TO PREDICT REOCCURRENCE OF DEFORMITY FOR CHILDREN WITH UNILATERAL CLUBFOOT." UKnowledge, 2018. https://uknowledge.uky.edu/khp_etds/55.

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Reoccurrence of deformity can affect upwards of 64% of children with clubfoot. The ability to use foot function as a measure of reoccurrence has not been previously assessed. The purpose of this investigation was to utilize foot pressure analysis to predict the probability of reoccurrence in children with unilateral clubfoot. Retrospective foot pressure data revealed predictive algorithms detecting the probability of experiencing any type of reoccurrence (overall reoccurrence) and for experiencing a tibialis anterior tendon transfer (TATT). The equation for overall reoccurrence reported sensitivity and specificity of 0.82 and 0.81 and the equation for TATT reported values of 0.81 and 0.84. These algorithms were then applied prospectively to a cohort of children with unilateral clubfoot. Interim sensitivity and specificity results at a 1.5-year follow-up demonstrate that the equations for overall reoccurrence and TATT were highly specific but not sensitive (0.84, 0.73 specificity; 0.11, 0 sensitivity). This is an indication that these algorithms were more accurate when identifying the absence of reoccurrence. However, these results may change as the prospective subjects continue to age. Overall, the results of this investigation show that foot pressure analysis can predict the presence/absence of reoccurrence. The algorithms developed herein have the potential to improve long and short-term outcomes for children with clubfoot. Providing clinicians with the probability of reoccurrence will improve their ability to be proactive during the treatment decision making process.
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Nguyen, Tuan Ngoc. "An algorithm for extracting the PPG Baseline Drift in real-time." Thesis, Edith Cowan University, Research Online, Perth, Western Australia, 2016. https://ro.ecu.edu.au/theses/1801.

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Photoplethysmography is an optical technique for measuring the perfusion of blood in skin and tissue arterial vessels. Due to its simplicity, accessibility and abundance of information on an individual’s cardiovascular system, it has been a pervasive topic of research within recent years. With these benefits however there are many challenges concerning the processing and conditioning of the signal in order to allow information to be extracted. One such challenge is removing the baseline drift of the signal, which is caused by respiratory rate, muscle tremor and physiological changes within the body as a response to various stimuli. Over the years there have been many methods developed in order to condition the signal such as Wavelet Transform, Cubic Spline Interpolation, Morphological Operators and Fourier-Based filtering techniques. All have their own individual benefits and drawbacks. These drawbacks are that they are unsuitable for real-time usage due to the computation power needed, or have the trade-off of being real-time at the cost of deforming the signal which is unideal for accurate analysis. This thesis aims to explore these techniques in order to develop an algorithm that can be used to condition the signal against the baseline drift in real-time, while being able to achieve good computational efficiency and the preservation of the signal form.
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Moya, Plana Antoine. "Recherche de biomarqueurs pronostiques dans le mélanome muqueux non opérable et/ou métastatique : Régulation traductionnelle de SOX10 par l’hexokinase 2 et modulation de l'agressivité tumorale dans le mélanome cutané Prognostic Value and Therapeutic Implications of Nodal Involvement in Head and Neck Mucosal Melanoma Evaluation of the Efficacy of Immunotherapy for Non-Resectable Mucosal Melanoma Oncologic Outcomes, Prognostic Factor Analysis and Therapeutic Algorithm Evaluation of Head and Neck Mucosal Melanomas in France Mélanomes cutanés cervico-faciaux Prognostic 18F-FDG PET Biomarkers in Metastatic Mucosal and Cutaneous Melanoma Treated with Immune Checkpoint Inhibitors Targeting PD-1 and CTLA-4." Thesis, université Paris-Saclay, 2020. http://www.theses.fr/2020UPASS069.

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Les mélanomes muqueux sont rares avec un potentiel métastatique important. L’immunothérapie est un traitement prometteur dans ce sous-type agressif de mélanome. L’analyse de biomarqueurs de réponse à une immunothérapie anti-PD1 chez 23 patients présentant un mélanome muqueux non opérable et/ou métastatique a montré que l’activation du complexe d’initiation de la traduction, eIF4F, était fortement prédictive de cette réponse. Cette activation a été mesurée par un test de proximité entre les sous-unités eIF4E et eIF4G. Les autres marqueurs admis, tels que l’expression tumorale de PD-L1 ou les caractéristiques de l’infiltrat lymphocytaire intra-tumoral, n’ont pas de valeur pronostique significative dans cette cohorte.La glycolyse anaérobie est la voie métabolique que la plupart des cellules tumorales privilégient lors de lacancérogenèse. Ce phénomène est appelé « effet Warburg ». Au cours de la mélanomagénèse, il existe un continuum entre l’expression croissante de l’hexokinase 2 (ou HK2, première enzyme de la glycolyse) et l’agressivité tumorale. Dans cette étude, nous avons montré que l’inhibition d’expression d’HK2 (par siARN) induisait, in vitro, une diminution majeure de la migration et de l’invasion tumorales indépendamment du métabolisme glucidique ou de l’expression initiale d’HK2. Par une technique de profilage des polysomes, nous avons observé que HK2 régulait la traduction de l’ARNm de SOX10, un facteur de transcription impliqué dans l’initiation et la progression du mélanome. Nous avons alors réalisé une immunoprécipitation de l’ARN après induction de liaisons protéine-ARN par du formaldéhyde, nous permettant ainsi de démontrer que la protéine HK2 se liait à l’ARNm de SOX10<br>Mucosal melanoma is a rare tumor with a high metastatic potential. Immunotherapy has promising results in this aggressive subtype of melanoma. In a cohort of 23 patients with non-resectable and/or metastatic mucosal melanoma who received anti-PD1 immunotherapy, we showed that the activation of the eukaryotic translation initiation complex, eIF4F, was a strong prognostic biomarker of response. This activation was assessed with a proximity ligation assay between eIF4E and eIF4G. The other biomarkers, such as the PD-L1 tumoral expression or the characteristics of tumor-infiltrating lymphocytes, had no prognostic value in this cohort.Aerobic glycolysis is usually the main metabolic pathway in tumor cells during cancerogenesis. This specificprocess is called “Warburg effect”. During melanomagenesis, we observed a positive correlation between the expression level of hexokinase 2 (HK2, first enzyme of glycolysis) and the tumor invasiveness. In this study, we showed that inhibition of HK2 expression (by siRNA) induced, in vitro, a major decrease of migration and invasion potential independently of the basal glycolytic metabolism or HK2 expression level in the cell lines. Moreover, performing a polysome profiling analysis, we demonstrated that HK2 was regulating the translation of SOX10 mRNA, a transcription factor involved in initiation and progression of melanoma. We, then, realized an RNA immunoprecipitation in formaldehyde and showed that HK2 was an RNA-binding protein, able to interact with the SOX10 mRNA
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Rojas, Rojas Teresa Milagros. "Particularités du carcinome hépatocellulaire au Pérou : étude clinique, génétique et de médecine intégrative." Thesis, Aix-Marseille, 2017. http://www.theses.fr/2017AIXM0549.

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Le cancer du foie est la deuxième cause de mortalité due au cancer dans le monde, avec près de 83% des cas et 84% des décès ayant lieu dans les pays en voie de développement. Le type histologique de cancer du foie le plus fréquemment répandu est le carcinome hépatocellulaire (HCC). Selon la littérature disponible, le HCC affecte électivement des sujets masculins de plus de 50 ans ayant développé préalablement une cirrhose hépatique. Nos objectifs étaient donc i) de confirmer au niveau moléculaire la singularité du HCC chez les patients péruviens, ii) d'évaluer les stratégies d'intervention chirurgicale dans le contexte clinique iii) d'étudier les pratiques de médecine traditionnelle, complémentaire et alternative (TCAM) chez les patients iv) d'étendre cette étude à d'autres pays en développement afin d'obtenir une vision plus globale de la problématique liée au cancer du foie. Nous avons montré que le HCC péruvien présentait un spectre de mutations unique. De plus, nous avons démontré que les arbres décisionnels thérapeutiques développés jusqu'alors ne sont pas adaptés au contexte clinique rencontré au Pérou, et qu'ils sont susceptibles d'être réévalués afin d'augmenter la proportion de patients pouvant être candidats à une intervention chirurgicale. Nous avons caractérisé le fait que la majorité des patients avec un HCC a recours à la phytothérapie de manière complémentaire et alternative. Enfin, nous avons réalisé une étude d'épidémiologie clinique préliminaire sur le cancer du foie au Cambodge. Nous avons décrit une situation clinique distincte de celle rencontrée au Pérou, mais qui nécessite également des recherches scientifiques et cliniques plus approfondies<br>Liver cancer is the second leading cause of cancer related death in the world. About 83% of liver cancer cases occur in the developing world. The preeminent histotype of liver cancer is hepatocellular carcinoma (HCC). According to the relevant literature, HCC is defined by patient profile corresponding grossly to cirrhotic males over 50 years old. The aims of the present work were thus to i) confirm at the molecular level the pecularity of Peruvian HCC; ii) evaluate the surgical intervention strategies for HCC in the clinical context encountered in Peru; iii) study the practices of traditional, complementary and alternative medicine ( TCAM) among patients; iv) widen the study to other low- and middle income countries in order to provide deeper insights on liver cancer. We found that Peruvian HCC displayed a unique mutation spectrum. Furthermore, we demonstrated that current therapeutic algorithms for liver cancer are not suited to the clinical context found in Peru. These therapeutic algorithms should be reevaluated in order to increase the number of patients who could be eligible for surgical intervention. Moreover, we characterized the fact that the majority of Peruvian HCC patients rely on phytotherapy in a complementary and alternative way. Finally, we undertook a preliminary clinical, epidemiological study on liver cancer in Cambodia. We delineated a clinical context distinct from the one described in Peru that also requires further clinical and scientific investigation
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Books on the topic "Therapeutic algorithms"

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Millikan, Keith W., Jonathan A. Myers, and Theodore J. Saclarides. Common surgical diseases: An algorithmic approach to problem solving. Springer, 2015.

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Amara, Lynn. Acute therapeutics for the homeopathic practitioner: A compendium of algorithm charts and flow charts. Amara, 1996.

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Vasquez, Alex. Integrative rheumatology ; concepts, algorithms, and therapeutics: Creating wellness while effectively managing acute and chronic musculoskeletal disorders. Natural Health Consulting Corp., 2006.

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W, Millikan Keith, Saclarides Theodore J. 1956-, and SpringerLink (Online service), eds. Common Surgical Diseases: An Algorithmic Approach to Problem Solving. Springer Science+Business Media, LLC, 2008.

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Berihanova, Rumisa, and Inessa Minenko. Complex non-drug correction of menopausal disorders in patients with metabolic syndrome. INFRA-M Academic Publishing LLC., 2021. http://dx.doi.org/10.12737/1599004.

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The monograph is devoted to the complex non-drug correction of menopausal disorders in patients with metabolic syndrome in the period of menopausal transition. Modern ideas about menopausal and metabolic syndromes are presented, a review of modern approaches to their treatment is carried out. &#x0D; A complex personalized system of non-drug correction of functional disorders in patients with metabolic syndrome and menopausal syndrome of mild and moderate severity in the period of menopausal transition is presented, including preformed therapeutic factors (vibrotherapy, chromotherapy, aeroionotherapy, musicotherapy (melotherapy), aromatherapy), physical therapy with pelvic floor muscle training, drinking balneotherapy, vitamins and minerals against the background of lifestyle modification.&#x0D; The algorithm of dynamic clinical and laboratory examination of women with menopausal disorders of mild and moderate severity and metabolic syndrome in the period of menopausal transition has been developed, including a general clinical examination, assessment of alimentary, thyroid, psycho-emotional, gynecological, urological statuses, the state of the intestinal microbiota, the function of the hypothalamic-pituitary complex, biochemical blood profile, hemostasis, levels of markers of inflammation, assessment of the state of the musculoskeletal system, sexual function, allowing to get an idea of the state of mental and physical health of patients, evaluate the effectiveness of the complex of measures, optimize therapeutic tactics.&#x0D; It is addressed to a wide range of readers interested in women's health. It can be useful for students, postgraduates, teachers of medical universities, obstetricians, gynecologists, endocrinologists, cardiologists, specialists of restorative medicine.
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Vasquez, Alex. Integrative orthopedics: Integrative, nutritional, botanical, and manipulative therapeutics with concepts, perspectives, algorithms, and protocols for the in-office diagnosis and management of the most common neuromusculoskeletal problems. 2nd ed. Integrative and Biological Medicine Research and Consulting, LLC, 2004.

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Quantitative neuroscience: Models, algorithms, diagnostics, and therapeutic applications. Kluwer Academic, 2004.

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Pardalos, P. M. Quantitative Neuroscience: Models, Algorithms, Diagnostics, and Therapeutic Applications. Springer London, Limited, 2013.

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Pardalos, P. M. Quantitative Neuroscience: Models, Algorithms, Diagnostics, and Therapeutic Applications. Springer, 2011.

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Pardalos, P. M. Quantitative Neuroscience: Models, Algorithms, Diagnostics, and Therapeutic Applications. Springer, 2013.

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Book chapters on the topic "Therapeutic algorithms"

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Negi, Pranshu C. B. S., Arun Bhatt, and Neeraj Sharma. "Cedrus Deodara Needle Oil and Bark Extract as Potential Therapeutic Candidate for Glaucoma." In Algorithms for Intelligent Systems. Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-33-6307-6_12.

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Sun, Jiayue, Shun Xu, Yang Liu, and Huaguang Zhang. "N-Level Hierarchy-Based Optimal Control to Develop Therapeutic Strategies for Ecological Evolutionary Dynamics Systems." In Adaptive Dynamic Programming. Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-99-5929-7_5.

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AbstractThis chapter mainly proposes an evolutionary algorithm and its first application to develop therapeutic strategies for Ecological Evolutionary Dynamics Systems (EEDS), obtaining the balance between tumor cells and immune cells by rationally arranging chemotherapeutic drugs and immune drugs. Firstly, an EEDS nonlinear kinetic model is constructed to describe the relationship between tumor cells, immune cells, dose, and drug concentration. Secondly, the N-Level Hierarchy Optimization (NLHO) algorithm is designed and compared with 5 algorithms on 20 benchmark functions, which proves the feasibility and effectiveness of NLHO. Finally, we apply NLHO into EEDS to give a dynamic adaptive optimal control policy, and develop therapeutic strategies to reduce tumor cells, while minimizing the harm of chemotherapy drugs and immune drugs to the human body. The experimental results prove the validity of the research method.
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Yeoman, Mark S., B. Daya Reddy, Deon Bezuidenhout, Hellmut C. Bowles, Peter Zilla, and Thomas Franz. "Development of a Fabric-Reinforced Porous Graft for Vascular Tissue Engineering Using Finite Element Methods and Genetic Algorithms." In Cardiovascular and Cardiac Therapeutic Devices. Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/8415_2013_162.

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Yeoman, Mark S., B. Daya Reddy, Deon Bezuidenhout, Hellmut C. Bowles, Peter Zilla, and Thomas Franz. "Errata to: Development of a Fabric-Reinforced Porous Graft for Vascular Tissue Engineering Using Finite Element Methods and Genetic Algorithms." In Cardiovascular and Cardiac Therapeutic Devices. Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/8415_2013_168.

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Tong, Pan, and Hua Li. "Mining Massive Genomic Data for Therapeutic Biomarker Discovery in Cancer: Resources, Tools, and Algorithms." In Big Data Analytics in Genomics. Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-41279-5_10.

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Khanna, Reena, and Brian G. Feagan. "The Role of Biomarkers in Treatment Algorithms for Ulcerative Colitis (UC)." In Quantitative Pharmacology and Individualized Therapy Strategies in Development of Therapeutic Proteins for Immune-Mediated Inflammatory Diseases. John Wiley & Sons, Inc., 2019. http://dx.doi.org/10.1002/9781119289234.ch2.

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Osmanoglu, Usame Omer. "The Use of Artificial Intelligence in the Diagnosis and Treatment of Diabetes." In Current Multidisciplinary Approach to Diabetes Mellitus Occurrence Mechanism. Nobel Tip Kitabevleri, 2023. http://dx.doi.org/10.69860/nobel.9786053359104.15.

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Artificial intelligence (AI) is increasingly transforming the landscape of diabetes diagnosis and treatment by leveraging data-driven approaches to enhance precision and efficiency in healthcare. AI algorithms analyze vast amounts of patient data, including medical records, genetic profiles, and real-time physiological metrics from wearable devices, to identify patterns and predict disease progression. In diagnostics, AI-powered systems can interpret complex datasets to facilitate early detection of diabetes and its complications, such as diabetic retinopathy and nephropathy, improving clinical outcomes through timely intervention. Furthermore, AI algorithms aid in personalized treatment strategies by optimizing insulin dosing regimens based on individual patient characteristics and response patterns. Machine learning models continue to evolve, offering healthcare providers decision support tools that streamline care delivery, enhance patient monitoring, and tailor therapeutic interventions to achieve better glycemic control and mitigate long-term complications of diabetes mellitus. As AI technologies advance, their integration into clinical practice holds promise for revolutionizing diabetes management, fostering proactive healthcare strategies, and ultimately improving patient outcomes.
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Schenone, Gustavo Emilio. "Therapeutic Considerations: Algorithm." In Injection-Induced Breast Siliconomas. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-24116-2_7.

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El-Dib, Mohamed, and Linda S. de Vries. "Neurophysiological Monitoring." In Neonatal Brain Injury. Springer Nature Switzerland, 2024. https://doi.org/10.1007/978-3-031-55972-3_16.

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AbstractEEG (electroencephalogram) is utilized to detect cortical cerebral electric activity. In neonates, both conventional EEG (cEEG) and a simplified form known as amplitude-integrated EEG (aEEG) hold significant value. Prolonged continuous EEG is recommended in high-risk scenarios and has been associated with improved seizure identification and outcomes. While aEEG aids in seizure detection, cEEG remains the gold standard for diagnosing seizures in neonates. aEEG is employed as a bedside tool for selecting infants with neonatal encephalopathy for therapeutic hypothermia, while both aEEG and cEEG are valuable for prognostication. Continuous EEG monitoring further improves seizure detection and outcome prediction for extremely preterm infants and critically ill infants. Utilization of neurophysiological monitoring in the NICU can be enhanced by the emerging automated analysis algorithms.
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"Therapeutic Attitudes and Therapeutic Algorithms." In Status Epilepticus. The MIT Press, 2006. http://dx.doi.org/10.7551/mitpress/6456.003.0039.

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Conference papers on the topic "Therapeutic algorithms"

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Liu, Xuan, Guohua Li, Yanshen Liao, Zishao Zhong, and Hang Wei. "A Geneformer-Based Model for Identifying Early Gastric Cancer Therapeutic Targets." In 2025 2nd International Conference on Algorithms, Software Engineering and Network Security (ASENS). IEEE, 2025. https://doi.org/10.1109/asens64990.2025.11011005.

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Venu, Sreelakshmy, Anbarasi Gunasekar, and Shalini Ganeshan. "Development of Molecular Docking Algorithms to Evaluate Therapeutic Potential of Ferulic Acid’s in Diabetic Wound Healing." In 2024 International Conference on Emerging Research in Computational Science (ICERCS). IEEE, 2024. https://doi.org/10.1109/icercs63125.2024.10894817.

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Annisa, J., M. A. Zulkifli, M. N. Leman, S. Mohamaddan, and H. Hazmi. "Optimizing PID-Based Controller Utilizing Hybrid Evolutionary Algorithmn in Electric Motor-Driven Exoskeletons for Therapeutic Locomotion of Stroke Patients." In 2024 IEEE 10th International Conference on Smart Instrumentation, Measurement and Applications (ICSIMA). IEEE, 2024. http://dx.doi.org/10.1109/icsima62563.2024.10675530.

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Segate, Riccardo Vecellio. "The “Medical Exception” to Emotion Detection Algorithms within the EU's Forthcoming AI Act: Regulatory Implications for Therapeutical Smart Cobotics." In 2024 IEEE 8th Forum on Research and Technologies for Society and Industry Innovation (RTSI). IEEE, 2024. http://dx.doi.org/10.1109/rtsi61910.2024.10761570.

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Enquero, Shreya Patchala, G. Sunil, Suvarna Sunil Kumar, Chunduri Lavanya, and Prateeksha Siddhanti. "Deep Neural Pretraining for Improving Diagnostic and Therapeutic Entity Recognition in Electronic Medical Records." In 2023 International Conference on Evolutionary Algorithms and Soft Computing Techniques (EASCT). IEEE, 2023. http://dx.doi.org/10.1109/easct59475.2023.10393025.

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Zanin, A., L. Mekhantyeva, A. Masalytin, and A. Enin. "DEVELOPMENT OF THERAPEUTIC AND DIAGNOSTIC ALGORITHMS FOR DAMAGE TO THE ORGANS OF THE URINARY SYSTEM IN THE CONTEXT OF MILITARY OPERATIONS." In TECHNOSPHERE SAFETY: MODERN SCIENTIFIC TRENDS, TECHNICAL AND ORGANIZATIONAL MEANS AND METHODS OF PROVISION, SPECIAL EDUCATION. FSBE Institution of Higher Education Voronezh State University of Forestry and Technologies named after G.F. Morozov, 2024. https://doi.org/10.58168/technosphere2024_61-71.

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The scientific article proposes the creation of a model of algorithms for first aid, diagnosis, evacuation and emergency surgical treatment in case of combined traumatic damage to the organs of the internal medicine system (kidneys and bladder) in the conditions of military operations. The paper analyzes statistical data obtained during various armed conflicts. The aim of the study is to standardize and develop a timely tactically significant algorithm for first aid, timely diagnosis, evacuation and further treatment tactics for combined injury of the urinary system (kidney injury, rupture of the bladder) in conditions of real military operations.
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Erriquez, Jessica, Martina Olivero, Gloria Mittica, et al. "Abstract LB-042: Xenopatients help in redefining medical therapeutic algorithms in high risk ovarian cancer." In Proceedings: AACR 107th Annual Meeting 2016; April 16-20, 2016; New Orleans, LA. American Association for Cancer Research, 2016. http://dx.doi.org/10.1158/1538-7445.am2016-lb-042.

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Sui, Yanan, and Joel W. Burdick. "Correlational Dueling Bandits with Application to Clinical Treatment in Large Decision Spaces." In Twenty-Sixth International Joint Conference on Artificial Intelligence. International Joint Conferences on Artificial Intelligence Organization, 2017. http://dx.doi.org/10.24963/ijcai.2017/389.

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We consider sequential decision making under uncertainty, the optimization over large decision space with noisy comparative feedback. This problem can be formulated as a K-armed Dueling Bandits problem where K is the total number of decisions. When K is very large, existing dueling bandits algorithms suffer huge cumulative regret before converging on the optimal arm. This paper studies the dueling bandits problem with a large number of dependent arms. Our problem is motivated by a clinical decision making process in large decision space. We propose an efficient algorithm CorrDuel for the problem which makes decisions to simultaneously deliver effective therapy and explore the decision space. Many sequential decision making problems with large and structured decision space could be facilitated by our algorithm. After evaluated the fast convergence of CorrDuel in analysis and simulation experiments, we applied it on a live clinical trial of therapeutic spinal cord stimulation. It is the first applied algorithm towards spinal cord injury treatments and experimental results show the effectiveness and efficiency of our algorithm.
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Rajat Mishra, Rajat Mishra, and Vandana Dixit Kaushik. "DEEP INTO ACCURACY: EXPLORING THE PERFORMANCE OF SKIN DETECTION ALGORITHMS IN DEEP LEARNING." In Computing for Sustainable Innovation: Shaping Tomorrow’s World. Innovative Research Publication, 2024. http://dx.doi.org/10.55524/csistw.2024.12.1.19.

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Skin diseases rank among the most prevalent medical conditions, given that the skin, being the outermost layer of the body, is susceptible to rapid affliction. Timely identification of these diseases is crucial to prevent them from progressing to life-threatening stages. This review explores diverse research endeavors employing deep learning technology for skin disease identification. It provides a brief overview of skin diseases, encompassing their types, datasets used for skin disease research, and techniques for data preprocessing. The review delves into the realm of deep learning, elucidating prominent methods adopted by researchers for diagnosing skin diseases. Our primary objective is to furnish a systematic literature review of skin disease detection, emphasizing the utilization of deep learning methodologies in recent research. Notably recognized for their heightened accuracy, our observations affirm that these deep learning methods in skin disease image recognition surpass the capabilities of dermatologists, various machine-based therapeutic strategies, and alternative classification methods.
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Zhu, Na, and Nathaniel S. Miller. "Assessment of Parkinson’s Disease Tremor and Correlation Analysis With Applied Signal Processing." In ASME 2019 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2019. http://dx.doi.org/10.1115/imece2019-10622.

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Abstract Accurate measurement and assessment of Parkinson’s disease (PD) tremor is important for patients, clinicians, and researchers to track changes in disease progression and the effectiveness of therapeutic interventions. This study measured resting, postural, and kinetic tremor from patient’s most-affected hand with accelerometers and gyrometers, thus the linear and rotational motions in the x, y, z directions were obtained. Data were collected when patients were both ON and OFF their anti-PD medications. A bandpass filter was applied to extract raw tremor information and several signal processing algorithms were used to analyze the data in both time and frequency domains, including the correlations between motions at different directions. The results of medication effectiveness on PD tremor and the correlational analyses will be discussed.
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Reports on the topic "Therapeutic algorithms"

1

Grace, Dr Golla Reethi Shiny, Dr Anu K., Dr Pratyusha Choudary G., and Dr M. v. PATTERN OF THE HEMATOLOGICAL PARAMETERS IN COVID-19 PATIENTS. World Wide Journals, 2023. http://dx.doi.org/10.36106/ijar/5106302.

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Background: The coronavirus (SARS CoV 2)-related viral disease COVID 19 causes acute respiratory disease with severe symptoms. Numerous biomarkers of infection and inammation have been found to inuence the severity of disease. Acute respiratory infection, fever, pneumonia, cough, tiredness, and inammation are frequent clinical ndings during hospitalisation. The severity of the disease and a possibility of disease progression can be determined by circulating biomarkers like TWBC count, NLR and CRP that reect inammation. This is a retrospective study conducted on eight Material and Methods: y COVID-19 positive patients admitted at Dr.Pinnamaneni Siddhartha Institute of Medical Sciences &amp; RF, ChinnaAvutapally from 1st January 2021 to 30th June 2021. Results: Among the 80 COVID 19 patients studied, there are 63% males and 37% females. 46% of patients showed leucocytosis, 43% showed increased NLR and 60 % showed raised CRP. Hematological parameters in COVID 19 are important for di Conclusion: agnosis, complication management, prognosis, and patient recovery. These parameters must be effectively integrated into clinical algorithms and therapeutic decision making in addition to clinical assessment
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