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http://www.jucs.org/jucs_14_16/intelligent_decision_support_in/jucs_14_16_2720_2736_lindgaard.pdf
Intelligent Decision Support in Medicine: back to Bayes? Gitte Lindgaard, Catherine Pyper, Monique Frize (Carleton University, Ottawa, Canada [email protected], {cpyper, mfrize}connect.carleton.ca)
https://dl.acm.org/citation.cfm?doid=1362550.1362554
We're upgrading the ACM DL, and would like your input. Please sign up to review new features, functionality and page designs.Cited by: 1
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.163.4668
CiteSeerX - Document Details (Isaac Councill, Lee Giles, Pradeep Teregowda): Abstract: Decision Support Systems are proliferating rapidly in many areas of human endeavour including clinical medicine and psychology. While these are typically based on rulebased systems, decision trees, or Artificial Neural Networks, this paper argues that Bayes’ Theorem can be applied fruitfully to support ...
http://www.jucs.org/jucs_14_16/intelligent_decision_support_in
Abstract: Decision Support Systems are proliferating rapidly in many areas of human endeavour including clinical medicine and psychology. While these are typically based on rule-based systems, decision trees, or Artificial Neural Networks, this paper argues that Bayes Theorem can be applied fruitfully to support expert decisions both in ...
https://core.ac.uk/display/36831246
Abstract. Decision Support Systems are proliferating rapidly in many areas of human endeavour including clinical medicine and psychology. While these are typically based on rule-based systems, decision trees, or Artificial Neural Networks, this paper argues that Bayes' Theorem can be applied fruitfully to support expert decisions both in dynamically changing situations requiring the system ...
https://core.ac.uk/display/36832878
Decision Support Systems (DSSs) are proliferating at an increasingly rapid pace in many areas of human endeavor including clinical medicine and psychology. These DSSs are typically based on Artificial Neural Networks (ANNs), many of which have been shown to perform very well (e.g. Ennett, 2003).Author: Gitte Lindgaard
https://en.wikipedia.org/wiki/Bayes_decision_theory
In probability theory and statistics, Bayes’s theorem (alternatively Bayes’s law or Bayes’s rule) describes the probability of an event, based on prior knowledge of conditions that might be related to the event.For example, if cancer is related to age, then, using Bayes’ theorem, a person's age can be used to more accurately assess the probability that they have cancer than can be done ...
https://www.medicinenet.com/script/main/art.asp?articlekey=10301
Dec 27, 2018 · Bayes theorem: A probability principle set forth by the English mathematician Thomas Bayes (1702-1761). Bayes' theorem is of value in medical decision-making and some of the biomedical sciences. Bayes' theorem is employed in clinical epidemiology to determine the probability of a particular disease in a group of people with a specific characteristic on the basis of the overall rate of that ...
https://www.intechopen.com/books/current-topics-in-public-health/bayesian-approach-in-medicine-and-health-management
May 15, 2013 · This chapter is an introduction to the modern world of Bayes procedures for professionals with a minimal background in biostatistics. In particular, we analyze the main theoretical aspects of the Bayesian approach and we review current thinking on the value of this approach as a decision-support system in medicine and health management.Cited by: 4
https://www.researchgate.net/publication/223942254_Does_Bayes_have_it_Decision_Support_Systems_in_diagnostic_medicine
Decision Support Systems in diagnostic medicine This paper aims to show how psychological research can contribute to the design of medical diagnostic Decision Support Systems (DSSs).
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