Relevant bibliographies by topics / Prognosing

Contents

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

Academic literature on the topic 'Prognosing'

Author: Grafiati
Published: 4 June 2021
Last updated: 7 February 2022

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Journal articles on the topic "Prognosing"

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Фещенко, Ю. І., Л. О. Яшина, К. В. Назаренко, В. І. Ігнатьєва, and С. Г. Опімах. "SEVERE COURSE OF BRONCHIAL ASTHMA PROGNOSING." Asthma and allergy 2019, no. 1 (2019): 9–14. http://dx.doi.org/10.31655/2307-3373-2019-1-9-14.

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Tomala, K., M. Trzak, and J. Kobylinska. "PROGNOSING STORAGE ABILITY OF 'GLOSTER' APPLES." Acta Horticulturae, no. 368 (July 1994): 578–85. http://dx.doi.org/10.17660/actahortic.1994.368.67.

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Kagan, Yurij, and Igor Lepeshkin. "The problem of prognosing of pesticide hazard." Toxicology Letters 88 (October 1996): 78. http://dx.doi.org/10.1016/s0378-4274(96)80282-7.

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Rebora, A. "Prognosing Melanomas: The Argyrophilic Nucleolar Organizer Region Approach." Dermatology 185, no. 3 (1992): 166–68. http://dx.doi.org/10.1159/000247440.

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Savenkova, Iryna, Mykola Didukh, Inna Chuhueva, and Iryna Litvinenko. "Chronopsychological mental development dysontogenesis prognosing in pre-school children." Electronic Journal of General Medicine 16, no. 2 (April 17, 2019): em110. http://dx.doi.org/10.29333/ejgm/108595.

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Карякина, O. Karyakina, Мартынова, N. Martynova, Басова, L. Basova, Кочорова, and L. Kochorova. "Using of Neural Network for Prognosing of Postoperation Complications." Journal of New Medical Technologies 22, no. 4 (November 15, 2015): 117–21. http://dx.doi.org/10.12737/17035.

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The paper presents an analysis of results of surgical treatment of patients with chronic lung disease. To predict the probability of postoperative complications, duration of treatment and the final outcome after surgical treatment for lung the authors used artificial neural networks (ANN). Currently in thoracic surgery practically there are no universally accepted prognostic systems, allowing with high degree of confidence to make the right decision in the treatment strategy for various lung diseases. The complexity of forecasting in this situation due to the fact that the most information is a subjective expert evaluation by a physician based on his knowledge and experience in the treatment of patients with lung disease. The results of the research proved that the modeling method based on ANN allows to solve problems of classification, optimization and forecasting and to give higher prediction accuracy in comparison with multivariate statistical analysis methods. The article shows that the use of ANN methods enables more accurately predict the risk of postoperative complications. This accelerates the work of specialists and facilitates to plan hospitals with high surgical activity.
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Dutta, Vibekananda, and Teresa Zielinska. "Prognosing Human Activity Using Actions Forecast and Structured Database." IEEE Access 8 (2020): 6098–116. http://dx.doi.org/10.1109/access.2020.2963933.

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Hu, Nan, Haojie Cheng, Kevin Zhang, and Randy Jensen. "Evaluating the Prognostic Accuracy of Biomarkers for Glioblastoma Multiforme Using The Cancer Genome Atlas Data." Cancer Informatics 16 (January 1, 2017): 117693511773484. http://dx.doi.org/10.1177/1176935117734844.

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Background: Glioblastoma multiforme (GBM) is the most common and aggressive primary brain tumor. Previous studies on GBM biomarkers focused on the effect of the biomarkers on overall survival (OS). Until now, no study has been published that evaluates the performance of biomarkers for prognosing OS. We examined the performance of microRNAs, gene expressions, gene signatures, and methylation that were previously identified to be prognostic. In addition, we investigated whether using clinical risk factors in combination with biomarkers can improve the prognostic performance. Methods: The Cancer Genome Atlas, which provides both biomarkers and OS information, was used in this study. The time-dependent receiver operating characteristic (ROC) curve was used to evaluate the prognostic accuracy. Results: For prognosis of OS by 2 years from diagnosis, the area under the ROC curve (AUC) of microRNAs, Mir21 and Mir222, was 0.550 and 0.625, respectively. When age was included in the risk prediction score of these biomarkers, the AUC increased to 0.719 and 0.701, respectively. The SAMSN1 gene expression attains an AUC of 0.563, and the “8-gene” signature identified by Bao achieves an AUC of 0.613. Conclusions: Although some biomarkers are significantly associated with OS, the ability of these biomarkers for prognosing OS events is limited. Incorporating clinical risk factors, such as age, can greatly improve the prognostic performance.
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Borzykh, V. E., and N. V. Lapik. "Modelling and Prognosing of Anthropogenic Accident in Oil and Gas Industry." Пожаровзрывобезопасность 19, no. 3 (June 2010): 31–35. http://dx.doi.org/10.18322/pvb.2010.19.03.31-35.

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Geyvandova, Natalya, and Alexandre Yagoda. "Mononuclear cells cytokines and interferonotherapy results prognosing in chronic viral hepatitis." Journal of Hepatology 36 (April 2002): 109. http://dx.doi.org/10.1016/s0168-8278(02)80384-1.

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Dissertations / Theses on the topic "Prognosing"

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Kinclová, Petra. "Statistická analýza finančních rizikových faktorů podniku." Master's thesis, Vysoké učení technické v Brně. Ústav soudního inženýrství, 2013. http://www.nusl.cz/ntk/nusl-232812.

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The master’s thesis deals with the usage of statistical analysis in the evaluation of the financial situation of the chosen company. The author focuses on the analysis of economic indocators, that are used in business practice for the assessment of the company financial situation. Summarized economic data are analyzed by financial and statistical analysis. The data comparism results to recommendations that may be impemented for company improvement. On the basis of historical data and trends prognosis the company gets specific picture about future situation and the effects on the market.
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Eibich, Peter, and Linn Burchert. "Prognosen - Nützliche Fiktionen." Universität Potsdam, 2012. http://opus.kobv.de/ubp/volltexte/2012/6054/.

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Vogt, Oliver. "Prognosen in Produkthierarchien." Lohmar Köln Eul, 2006. http://deposit.d-nb.de/cgi-bin/dokserv?id=2906164&prov=M&dok_var=1&dok_ext=htm.

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Tapson, J. S. "Prognosis after donor nephrectomy." Thesis, University of Newcastle Upon Tyne, 1987. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.382508.

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Jones, David John. "Prognosis in colorectal cancer." Thesis, University of Liverpool, 1988. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.235501.

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Perel, Pablo Andraes. "Prognosis in traumatic brain injury." Thesis, London School of Hygiene and Tropical Medicine (University of London), 2009. http://researchonline.lshtm.ac.uk/1635515/.

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Introduction: The general purpose of this thesis was to study prognosis in traumatic brain injury (TBI) patients, with the aim of providing useful and practical information in clinical practice and clinical research. The specific objectives were: to develop and validate practical prognostic models for TBI patients and to assess the validity of the Modified Oxford Handicap Scale (mOHS) for predicting disability at six months. Methods: A survey was first conducted to understand the importance of prognostic information among physicians. A systematic review of prognostic models for TBI patients was then carried out. Prognostic models were developed using data from a cohort of 10,008 TBI patients (CRASH trial) and validated in a cohort of 8,509 TBI patients (IMPACT study). Two focus groups and a survey were conducted to develop a paper-based prognostic score card. The correlation between the mOHS and the Glasgow Outcome Scale (GOS) was assessed, the validity of different mOHS dichotomies was assessed, and the discriminative ability of the mOHS to predict GOS was evaluated. Results: Doctors considered prognostic information to be very important in the clinical management of TBI patients, and believed that an accurate prognostic model would change their current clinical practice. Many prognostic models for TBI have been published, but they have many methodological flaws which limit their validity. Valid prognostic models for patients from high income countries and low & middle income .countries were developed and made available as a web calculator, and as a paper based score card. The mOHS was strongly correlated with and was predictive of GOS at six months. Conclusion: The prognostic models developed are valid and practical to use in the clinical setting. The association between mOHS and GOS suggest that the mOHS could be used for interim analysis in randomised clinical trials in TBI patients, for dealing with loss to follow-up, or could be used as simple tool to inform patients and relatives about their prognosis at hospital discharge.
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Biasci, Daniele. "Predicting prognosis in Crohn's disease." Thesis, University of Cambridge, 2017. https://www.repository.cam.ac.uk/handle/1810/270034.

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Elwes, R. D. C. "The early prognosis of epilepsy." Thesis, University of Edinburgh, 1988. http://hdl.handle.net/1842/18865.

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Ruge, Marcus. "Prognosen mit dynamischen Strukturgleichungsmodellen : ein Ausblick." Universität Potsdam, 2011. http://opus.kobv.de/ubp/volltexte/2012/5850/.

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Die vorliegende Untersuchung gibt einen Ausblick auf Prognosemöglichkeiten mit dynamischen Strukturgleichungsmodellen. Die Analyse komplexer Systeme mit umfangreichen Datensätzen und die Erkennung relevanter Muster erfordern die Verwendung moderner statistischer Verfahren. DPLS-Modelle, eine Variante der Strukturgleichungsmodelle mit Latenten Variablen, werden methodisch erweitert, um mehrere zeitliche Verzögerungsstufen gleichzeitig modellieren zu können. Die Modelle versuchen, zahlreiche latente Einflussfaktoren und ihre Wechselwirkungen zu identifizieren. Als Daten werden rund 80 Indikatoren aus 20 Quellen verwendet, um Stimmungen, Erwartungen und wirtschaftlich relevanten Größen zu operationalisieren und zeitliche Prognosemöglichkeiten zu evaluieren. Für kürzere Zeiträume von sechs Monaten sind Stimmungen und Erwartungen die besten verfügbaren Prognosevariablen. Dieser Beitrag ist entstanden im Rahmen eines Vortrages im gemeinsamen Forschungsseminar mit der Staatlichen Universität für Wirtschaft und Finanzen Sankt Petersburg Finec im Dezember 2010.
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Quyen, Nguyen Than Ha. "Diagnosis and prognosis of severe dengue." Thesis, Open University, 2011. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.539411.

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Books on the topic "Prognosing"

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Coburn, Tom A. Prognosis. [Washington, D.C.]: [Sen. Tom Coburn], 2014.

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1949-, Figal Günter, and Knapp Georg, eds. Prognosen. Tübingen: Attempto Verlag, 2001.

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Jeff, Gottesfeld, and Copyright Paperback Collection (Library of Congress), eds. Prognosis, heartbreak. New York: Berkley Jam Books, 2002.

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Inman, Daniel J., Charles R. Farrar, Vicente Lopes, and Valder Steffen, eds. Damage Prognosis. Chichester, UK: John Wiley & Sons, Ltd, 2005. http://dx.doi.org/10.1002/0470869097.

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Feindt, Michael, and Ulrich Kerzel. Prognosen bewerten. Berlin, Heidelberg: Springer Berlin Heidelberg, 2015. http://dx.doi.org/10.1007/978-3-662-44683-6.

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Chugal, Nadia, and Louis M. Lin, eds. Endodontic Prognosis. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-42412-5.

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Naim, Jack. Diagnosis 2: Prognosis. Bandar Baru Bangi, Selangor: DuBook Press Sdn. Bhd., 2015.

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Thiele, Jens. Kombination von Prognosen. Heidelberg: Physica, 1993.

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Koselleck, Reinhart. Aceleración, prognosis y secularización. Valencia: Pre-textos, 2003.

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Breytenbach, W. J. The ANC: Future prognosis. Belville, South Africa: University of Stellenbosch, Institute for Futures Research, 1989.

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Book chapters on the topic "Prognosing"

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Gómez-López, María Teresa, Luisa Parody, Rafael M. Gasca, and Stefanie Rinderle-Ma. "Prognosing the Compliance of Declarative Business Processes Using Event Trace Robustness." In On the Move to Meaningful Internet Systems: OTM 2014 Conferences, 327–44. Berlin, Heidelberg: Springer Berlin Heidelberg, 2014. http://dx.doi.org/10.1007/978-3-662-45563-0_19.

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Kukar, Matjaž, Nikola Bešič, Igor Kononenko, Marija Auersperg, and Marko Robnik-Šikonja. "Prognosing the Survival Time of Patients with Anaplastic Thyroid Carcinoma using Machine Learning." In Intelligent Data Analysis in Medicine and Pharmacology, 115–29. Boston, MA: Springer US, 1997. http://dx.doi.org/10.1007/978-1-4615-6059-3_7.

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Romanij, Stanislav F., and Michael A. Reznikov. "Dielectric Spectrometry as a Method of Testing and Prognosing of Polymeric Composite Qualities." In MICC 90, 1305–8. Dordrecht: Springer Netherlands, 1991. http://dx.doi.org/10.1007/978-94-011-3676-1_249.

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Kvist, Thomas. "Prognosis." In Apical Periodontitis in Root-Filled Teeth, 103–16. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-57250-5_9.

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Picano, Eugenio. "Prognosis." In Stress Echocardiography, 239–51. Berlin, Heidelberg: Springer Berlin Heidelberg, 2003. http://dx.doi.org/10.1007/978-3-662-05096-5_21.

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McConn, Ryan D., and Magdalena Anitescu. "Prognosis." In Fibromyalgia, 51–69. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-15820-4_4.

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Schaaf, Helmut. "Prognosen." In Morbus Menière, 99–104. Berlin, Heidelberg: Springer Berlin Heidelberg, 1998. http://dx.doi.org/10.1007/978-3-662-08860-9_9.

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Schaaf, Helmut. "Prognosen." In Morbus Menière, 77–78. Berlin, Heidelberg: Springer Berlin Heidelberg, 1995. http://dx.doi.org/10.1007/978-3-662-08861-6_10.

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Lee, Sungnack, Dongsik Bang, Eun-So Lee, and Seonghyang Sohn. "Prognosis." In Behçet’s Disease, 71. Berlin, Heidelberg: Springer Berlin Heidelberg, 2001. http://dx.doi.org/10.1007/978-3-642-56455-0_10.

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Lacoius-Petruccelli, Alberto. "Prognosis." In Perinatal Asphyxia, 37–49. Boston, MA: Springer US, 1987. http://dx.doi.org/10.1007/978-1-4613-1807-1_6.

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Conference papers on the topic "Prognosing"

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M. Borodulin, E. "Carbonatic builds prognosing by method seismic inversion." In 9th EAGE International Conference on Geoinformatics - Theoretical and Applied Aspects. European Association of Geoscientists & Engineers, 2010. http://dx.doi.org/10.3997/2214-4609.201402767.

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V. Makarov, V., I. A. Mushin, and A. V. Mikhaltsev. "Seismoformational Prognosing of Carbonate Reservoirs Capacity Properties." In 57th EAEG Meeting. Netherlands: EAGE Publications BV, 1995. http://dx.doi.org/10.3997/2214-4609.201409751.

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Lin, Linyu, Pascal Rouxelin, Paridhi Athe, Nam Dinh, and Jeffrey Lane. "Development and Assessment of Data-Driven Digital Twins in a Nearly Autonomous Management and Control System for Advanced Reactors." In 2020 International Conference on Nuclear Engineering collocated with the ASME 2020 Power Conference. American Society of Mechanical Engineers, 2020. http://dx.doi.org/10.1115/icone2020-16813.

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Abstract A critical component of the autonomous control system is the implementation of digital twin (DT) for diagnosing the conditions and prognosing the future transients of physical components or systems. The objective is to achieve an accurate understanding and prediction of future behaviors of the physical components or systems and to guide operating decisions by an operator or an autonomous control system. With specific requirements in the functional, interface, modeling, and accuracy, DTs are developed based on operational and simulation databases. As one of the modeling methods, data-driven methods have been used for implementing DTs since they have more adaptive forms and are able to capture interdependencies that can be overlooked in model-based DTs. To demonstrate the capabilities of DTs, a case study is designed for the control of the EBR-II sodium-cooled fast reactor during a single loss of flow accident, where either a complete or a partial loss of flow in one of the two primary sodium pumps is considered. Based on the definition of DTs and the design of autonomous control system, DTs for diagnosis and prognosis are implemented by training feedforward neural networks with suggested inputs, training parameters, and knowledge base. Furthermore, inspired by the validation and uncertainty quantification scheme for scientific computing, a list of sources of uncertainty in input variables, training parameters, and knowledge base is formulated. The objective is to assess qualitative impacts of different sources of uncertainty on the DT errors. It is found that the performance of DT for diagnosis and prognosis satisfies the acceptance criteria within the training databases. Meanwhile, the accuracy of DTs for diagnosis and prognosis is highly affected by multiple sources of uncertainty.
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Kiebish, Michael, Jennifer Cullen, Amina Ali, Leonardo O. Rodrigues, Emily Y. Chen, Eric Milliman, Lixia Xang, et al. "Abstract 3595: A panel of serum proteins, metabolite and lipid for prognosing prostate cancer progression." In Proceedings: AACR Annual Meeting 2018; April 14-18, 2018; Chicago, IL. American Association for Cancer Research, 2018. http://dx.doi.org/10.1158/1538-7445.am2018-3595.

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Ferreira, Tiago, Harrison Brewton, Loris D'Antoni, and Alexandra Silva. "Prognosis." In SIGCOMM '21: ACM SIGCOMM 2021 Conference. New York, NY, USA: ACM, 2021. http://dx.doi.org/10.1145/3452296.3472938.

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Mohammadpour, Javad, Karolos M. Grigoriadis, Matthew A. Franchek, and Benjamin J. Zwissler. "A Survey on Failure Prognosis Research: Theory and Applications." In ASME 2006 International Mechanical Engineering Congress and Exposition. ASMEDC, 2006. http://dx.doi.org/10.1115/imece2006-15044.

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The paper presents a survey of recent advances in the area of failure prognosis and highlights some of the engineering applications in this area. The theoretical aspects of data-driven and model-based prognosis and damage modeling are summarized. The paper also reviews a recently proposed intelligent modelbased diagnosis/prognosis structure and its components. Finally, some of the important industrial applications, in which prognosis techniques have been employed for anticipating failure occurrence and determining useful remaining life are discussed.
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Pawar, Sanket. "Framework Standard for Prognosis: An Approach for Effective Prognosis Implementation." In Symposium on International Automotive Technology 2019. 400 Commonwealth Drive, Warrendale, PA, United States: SAE International, 2019. http://dx.doi.org/10.4271/2019-26-0364.

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Wang, Pingfeng, Byeng D. Youn, and Chao Hu. "Concurrent Design of Functional Reliability and Failure Prognosis for Engineered Resilience." In ASME 2013 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2013. http://dx.doi.org/10.1115/detc2013-12593.

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This paper presents a new system design platform and approaches leading to the development of resilient engineered systems through integrating design of system functions and prognosis of function failures in a unified design framework. Failure prognosis plays an increasingly important role in complex engineered systems since it detects, diagnoses, and predicts the system-wide effects of adverse events, therefore enables a proactive approach to deal with system failures at the life cycle use phase. However, prognosis of system functional failures has been largely neglected in the past at early system design stage, mainly because quantitative analysis of failure prognosis in the early system design stage is far more challenging than these activities themselves that have been mainly carried out at the use phase of a system life cycle. In this paper, a generic mathematical formula of resilience and predictive resilience analysis will be introduced, which offers a unique way to consider lifecycle use phase failure prognosis in the early system design stage and to systematically analyze their costs and benefits, so that it can be integrated with system function designs concurrently to generate better overall system designs. Engineering design case studies will be used to demonstrate the proposed design for resilience methodology.
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Armstrong, L. R., P. Berrett, and E. Zablocki. "Diesel Engine Power Prognosis." In SAE International Congress and Exposition. 400 Commonwealth Drive, Warrendale, PA, United States: SAE International, 1985. http://dx.doi.org/10.4271/850548.

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Pei, Hai-Long, Douglas Brown, and George Vachtsevanos. "Prognosis-enhanced reconfiguration control." In 2010 International Conference on Networking, Sensing and Control (ICNSC). IEEE, 2010. http://dx.doi.org/10.1109/icnsc.2010.5461542.

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Reports on the topic "Prognosing"

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Bogdonoff, Seymour M. Hypersonic Flight Vehicles: Perspective and Prognosis,. Fort Belvoir, VA: Defense Technical Information Center, January 1999. http://dx.doi.org/10.21236/ada370547.

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Brooks, James D., and Ziding Feng. Validation of Biomarkers for Prostate Cancer Prognosis. Fort Belvoir, VA: Defense Technical Information Center, October 2012. http://dx.doi.org/10.21236/ada570054.

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Brooks, James D., and Ziding Feng. Validation of Biomarkers for Prostate Cancer Prognosis. Fort Belvoir, VA: Defense Technical Information Center, October 2013. http://dx.doi.org/10.21236/ada594132.

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Brooks, James D., and Ziding Feng. Validation of Biomarkers for Prostate Cancer Prognosis. Fort Belvoir, VA: Defense Technical Information Center, December 2014. http://dx.doi.org/10.21236/ada616329.

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Feng, Ziding, and James D. Brooks. Validation of Biomarkers for Prostate Cancer Prognosis. Fort Belvoir, VA: Defense Technical Information Center, October 2014. http://dx.doi.org/10.21236/ada621052.

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Krishna, Kala, Ataman Ozyildirim, and Norman Swanson. Trade, Investment, and Growth: Nexus, Analysis, and Prognosis. Cambridge, MA: National Bureau of Economic Research, December 1998. http://dx.doi.org/10.3386/w6861.

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Resau, James H. Molecular Based Imaging Determination of Breast Cancer Prognosis. Fort Belvoir, VA: Defense Technical Information Center, June 2002. http://dx.doi.org/10.21236/ada407431.

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Melbye, Mads. Risk Factors for Breast Cancer and its Prognosis. Fort Belvoir, VA: Defense Technical Information Center, October 1997. http://dx.doi.org/10.21236/ada340845.

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Bouton, Jr, and Edwin H. High-Level Nuclear Waste Disposal: Policy and Prognosis. Fort Belvoir, VA: Defense Technical Information Center, April 1992. http://dx.doi.org/10.21236/ada262251.

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Filiz, Ibrahim, Jan René Judek, Marco Lorenz, and Markus Spiwoks. Hüftsteife Aktienmarktanalysten. Sonderforschungsgruppe Institutionenanalyse, February 2021. http://dx.doi.org/10.46850/sofia.9783941627895.

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Wenn die Variabilität der Wirklichkeit systematisch unterschätzt wird, kann dies im Bereich der Aktienmarktprognose zu sehr kostenträchtigen Fehleinschätzungen beitragen. Die Zuverlässigkeit von Aktienmarktprognosen wird nur selten untersucht. Zwar liegt eine große Zahl von Studien zu Gewinnprognosen (pretax profit forecasts) vor (vgl. Ramnath, Rock & Shane, 2008), aber Untersuchungen der Prognosen von Aktienkursen, Aktienindizes oder Aktienrenditen sind nach wie vor rar. Deshalb wendet sich die vorliegende Studie der Betrachtung von Aktienindexprognosen zu. Es handelt sich um Prognosen des Deutschen Aktienindex (DAX), des Dow Jones Industrial Index (DJI) und des Euro Stoxx 50 (SX5E), die im Zeitraum von 1992 bis 2020 in den deutschen Tagesbeziehungsweise Wirtschaftszeitungen „Handelsblatt“ (HB) und „Frankfurter Allgemeine Zeitung“ (FAZ) veröffentlicht werden. Es handelt sich dabei um Prognosen mit Prognosehorizonten von sechs und zwölf Monaten, die regelmäßig von deutschen und internationalen Bankhäusern erstellt werden. In der vorliegenden Studie wird die Frage aufgeworfen, ob das Verhalten der betrachteten Aktienmarktanalysten der von Ogburn (1934) beschriebenen Charakteristik des Konservatismus entspricht und ob die Prognosen als tauglich oder als untauglich zu beurteilen sind.
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You might also be interested in the extended bibliographies on the topic 'Prognosing' for particular source types:
Journal articles Dissertations / Theses Books
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