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Clinical evidence framework for Bayesian networks
- Source :
- Knowledge and Information Systems. 50:117-143
- Publication Year :
- 2016
- Publisher :
- Springer Science and Business Media LLC, 2016.
-
Abstract
- There is poor uptake of prognostic decision support models by clinicians regardless of their accuracy. There is evidence that this results from doubts about the basis of the model as the evidence behind clinical models is often not clear to anyone other than their developers. In this paper, we propose a framework for representing the evidence-base of a Bayesian network (BN) decision support model. The aim of this evidence framework is to be able to present all the clinical evidence alongside the BN itself. The evidence framework is capable of presenting supporting and conflicting evidence, and evidence associated with relevant but excluded factors. It also allows the completeness of the evidence to be queried. We illustrate this framework using a BN that has been previously developed to predict acute traumatic coagulopathy, a potentially fatal disorder of blood clotting, at early stages of trauma care.
- Subjects :
- Decision support system
Blood clotting
Knowledge engineering
Bayesian network
02 engineering and technology
Evidence-based medicine
computer.software_genre
Trauma care
Data science
Clinical decision support system
Human-Computer Interaction
03 medical and health sciences
0302 clinical medicine
Artificial Intelligence
Hardware and Architecture
Clinical evidence
0202 electrical engineering, electronic engineering, information engineering
020201 artificial intelligence & image processing
030212 general & internal medicine
Data mining
Psychology
computer
Software
Information Systems
Subjects
Details
- ISSN :
- 02193116 and 02191377
- Volume :
- 50
- Database :
- OpenAIRE
- Journal :
- Knowledge and Information Systems
- Accession number :
- edsair.doi...........437286712e18287e703793677c2c3de1