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https://arxiv.org/pdf/1211.2126
application of a Medical Decision Support System (MDSS). This system has to make dynamic decision on temporal data. We use dynamic Bayesian network (DBN) to model this dynamic process. It is a temporal reasoning within a real-time environment; we are interested in the Dynamic Decision Support Systems in healthcare domain (MDDSS).Cited by: 16
https://ocw.mit.edu/courses/health-sciences-and-technology/hst-951j-medical-decision-support-spring-2003/lecture-notes/lecture5.pdf
Bayesian Networks Representation and Reasoning Marco F. Ramoni Children’s Hospital Informatics Program Harvard Medical School HST 951 (2003) Harvard-MIT Division of Health Sciences and Technology HST.951J: Medical Decision Support. Introduction Bayesian network are a knowledge representation formalism for reasoning under uncertainty.
https://www.bayesia.com/webinar-diagnostic-decision-support-with-bayesian-networks
Diagnostic Decision Support with Bayesian Networks. Recorded on February 9, 2018. Webinar Materials. Presentation Slides ... Structural Coefficient Analysis for Bayesian network model optimization. ... Diagnostic Decision Support with Bayesian Networks; Bayesian Networks—Artificial Intelligence for Research, Analytics, and Reasoning ...
https://onlinelibrary.wiley.com/doi/abs/10.1111/exsy.12089
Sep 21, 2014 · Bayesian network construction using a fuzzy rule based approach for medical decision support. Vasilios Zarikas. E-mail address: [email protected]. Department of Electrical Engineering, Academic Technology Institute of Central Greece, (ATEI), 3rd km Old National Road, Lamia‐Athens, Lamia, 35100 Greece ...Cited by: 13
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4839499/
Objectives. 1) To develop a rigorous and repeatable method for building effective Bayesian network (BN) models for medical decision support from complex, unstructured and incomplete patient questionnaires and interviews that inevitably contain examples of repetitive, redundant and contradictory responses; 2) To exploit expert knowledge in the BN development since further data acquisition is ...Cited by: 85
Post navigation. Sample Page. Overview
https://arxiv.org/pdf/1211.2126
application of a Medical Decision Support System (MDSS). This system has to make dynamic decision on temporal data. We use dynamic Bayesian network (DBN) to model this dynamic process. It is a temporal reasoning within a real-time environment; we are interested in the Dynamic Decision Support Systems in healthcare domain (MDDSS).Cited by: 16
https://ocw.mit.edu/courses/health-sciences-and-technology/hst-951j-medical-decision-support-spring-2003/lecture-notes/lecture5.pdf
Bayesian Networks Representation and Reasoning Marco F. Ramoni Children’s Hospital Informatics Program Harvard Medical School HST 951 (2003) Harvard-MIT Division of Health Sciences and Technology HST.951J: Medical Decision Support. Introduction Bayesian network are a knowledge representation formalism for reasoning under uncertainty.
https://www.bayesia.com/webinar-diagnostic-decision-support-with-bayesian-networks
Diagnostic Decision Support with Bayesian Networks. Recorded on February 9, 2018. Webinar Materials. Presentation Slides ... Structural Coefficient Analysis for Bayesian network model optimization. ... Diagnostic Decision Support with Bayesian Networks; Bayesian Networks—Artificial Intelligence for Research, Analytics, and Reasoning ...
https://onlinelibrary.wiley.com/doi/abs/10.1111/exsy.12089
Sep 21, 2014 · Bayesian network construction using a fuzzy rule based approach for medical decision support. Vasilios Zarikas. E-mail address: [email protected]. Department of Electrical Engineering, Academic Technology Institute of Central Greece, (ATEI), 3rd km Old National Road, Lamia‐Athens, Lamia, 35100 Greece ...Cited by: 13
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4839499/
Objectives. 1) To develop a rigorous and repeatable method for building effective Bayesian network (BN) models for medical decision support from complex, unstructured and incomplete patient questionnaires and interviews that inevitably contain examples of repetitive, redundant and contradictory responses; 2) To exploit expert knowledge in the BN development since further data acquisition is ...Cited by: 85
http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0082349
Bayesian Networks for Clinical Decision Support in Lung Cancer Care Survival prediction and treatment selection in lung cancer care are characterised by high levels of uncertainty.
https://www.bayesia.com/bayesian-networks-examples
Musson: Decision Support in Extreme Environments — Designing a Medical Care Support System for a Mission to Mars; Scott: Phase Based Statistics from Direct Numerically Simulated Imagery of Sediment-Laden Oscillatory Flow for Bayesian Belief Network Analysis; Sharrock: An Application of Bayesian Networks to Yield Prediction in Portuguese ...
https://www.sciencedirect.com/science/article/pii/S0010482514000961
This paper proposes a Bayesian Network (BN) decision model for supporting the diagnosis of dementia, AD and MCI. The proposed BN can be used for building clinical decision support systems (CDSS) to help in the diagnosis of such diseases. BNs are well-suited for representing uncertainty and causality, which are both present in the clinical domain.Cited by: 109
https://dl.acm.org/citation.cfm?id=2883363
<author>Wagholikar, K.B.</author>, S.Vijayraghavan and A.W.Deshpande 2009 Fuzzy naive Bayesian model for medical diagnostic decision support, in Engineering in Medicine and Biology Society, Annual International Conference of the IEEE, pp.3409-3412.Cited by: 13
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