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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://www.ncbi.nlm.nih.gov/pubmed/29503749
Objectives: In this study, a clinical decision support system was developed to help general practitioners assess the need for orthodontic treatment in patients with permanent dentition. Methods: We chose a Bayesian network (BN) as the underlying model for assessing the need for orthodontic treatment.Cited by: 5
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://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://www.researchgate.net/publication/322705466_Decision_Support_System_for_Hepatitis_Disease_Diagnosis_using_Bayesian_Network
A Clinical Decision Support System (CDSS) to assess suspicion of a disease would avoid unnecessary cost of medical diagnosis. Heart Failure (HF) is a complex clinical syndrome of cardiac disorder.
http://ceur-ws.org/Vol-949/kese8-02_07.pdf
Bayesian network, in the context of a knowledge-based software development. 1 Introduction Knowledge-based systems (KBSs) are characterized by their high risk, loose definition, poor structure and subjective requirements. These software systems were introduced in the early 1970s as expert systems from the field of artificial intelligence (AI) research.Cited by: 6
https://www.bayesialab.com/
Built on the foundation of the Bayesian network formalism, BayesiaLab 9 is a powerful desktop application (Windows, macOS, Linux/Unix) with a highly sophisticated graphical user interface. It provides scientists a comprehensive “lab” environment for machine learning, knowledge modeling, diagnosis, analysis, simulation, and optimization.
https://strathprints.strath.ac.uk/70093/
A decision support system for scour management of road and railway bridges based on Bayesian networks Maroni, Andrea and Tubaldi, Enrico and Val, Dimitri and McDonald, Hazel and Lothian, Stewart and Riches, Oliver and Zonta, Daniele ( 2019 ) A decision support system for scour management of road and railway bridges based on Bayesian networks.
https://ui.adsabs.harvard.edu/abs/2012arXiv1211.2126L/abstract
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).
https://pambayesian.org/bayesian-network-basics/
An overview of Bayesian networks. Data collection and decision making are major activities across the entire healthcare domain. Healthcare professionals typically collect patients’ personal information, such as symptoms, physical characteristics and medical history to support …
http://ceur-ws.org/Vol-949/kese8-02_07.pdf
of the network itself and network capabilities, such that inference from observed values of some variables. In particular, the Elvira system [10] is tool to construct probabilistic decision support systems. Elvira works with Bayesian networks and influence diagrams and can operate with discrete, continuous and temporal variables.
https://arxiv.org/abs/1301.1444
The Antitrust Authority's decision process is modelled using a Bayesian network where both the relational structure and the parameters of the model are estimated from a data set provided by the Authority itself. A number of economic variables that influence this decision process are also included in …
https://events.eventact.com/Ortra/IEM2010/Abstracts/199/50212/144.pdf
OPTIMIZATION BY TARGETED BAYESIAN NETWORK IN DECISION SUPPORT SYSTEMS A. Gruber and I. Ben-Gal Department of Industrial Engineering, Faculty of Engineering, Tel Aviv University, Ramat-Aviv, Tel-Aviv 69978, Israel E-mail: [email protected] / [email protected] ABSTRACT We present a Bayesian network learning method that can support ...
https://link.springer.com/chapter/10.1007%2F978-3-642-11688-9_20
A distinguishing feature of this network is the large amount of variables in the model. The second one involves an application for petrophysical decision support to determine the mineral content of a well, based on borehole measurements. This model differs from standard Bayesian networks in terms of its continuous variables and nonlinear relations.
http://www.iemss.org/iemss2010/papers/S24/S.24.12.The%20value%20of%20using%20Bayesian%20Networks%20in%20Environmental%20Decision%20Support%20Systems%20to%20support%20natural%20resource%20management%20-%20WENDY%20MERRITT.pdf
W.S. Merritt et al. / The value of using Bayesian Networks in Environmental Decision Support Systems to support natural resource management. A similar process is …
https://link.springer.com/chapter/10.1007%2F978-981-10-3310-0_18
Bayesian network was applied to assess the influences of the factors, and accordingly weightage and ranking of the contributing factors for landslide have been calculated. Finally, using multi-criteria decision support system (MCDSS) in GIS environment, landslide-risk zonation of the Darjeeling district has been prepared.
https://www.ukessays.com/essays/computer-science/types-of-clinical-decision-support-system-computer-science-essay.php
Since Clinical decision support system is a kind of decision support system that is design to assist clinician in decision making tasks. The architecture design of decision support system always consists of two major sub-systems which is human decision maker and computer systems. ... 4.2 Bayesian Network. Bayesian Network shows a set of ...
https://www.researchgate.net/publication/276203801_Metamodeling_of_Bayesian_networks_for_decision-support_systems_development
Metamodeling of Bayesian networks for decision-support systems development ... Bayesian network for decision-support on pest management of tomato fruit …
https://www.bayesfusion.com/bayesian-networks/
The theoretical minimum. Bayesian networks are acyclic directed graphs that represent factorizations of joint probability distributions. Every joint probability distribution over n random variables can be factorized in n! ways and written as a product of probability distributions …
https://www.hindawi.com/journals/ads/2011/425820/
Furthermore, we provide an expert system capable of supporting the enterprise decisional processes and a semantic engine which performs intelligent search on the enterprise knowledge bases. The decision support process exploits the Bayesian networks model to improve business planning process when performed under uncertainty.
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