Value of information analysis for interventional and counterfactual Bayesian networks in forensic medical sciences

2016-01-01
Constantinou, Anthony Costa
Yet, Barbaros
Fenton, Norman
Neil, Martin
Marsh, William
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Objectives: Inspired by real-world examples from the forensic medical sciences domain, we seek to determine whether a decision about an interventional action could be subject to amendments on the basis of some incomplete information within the model, and whether it would be worthwhile for the decision maker to seek further information prior to suggesting a decision.
Causal Inference, Bayesian Networks, Interventional Analysis, Counterfactual Analysis, Value Of Information, Forensic Medicine
https://hdl.handle.net/11511/56304
ARTIFICIAL INTELLIGENCE IN MEDICINE
Graduate School of Informatics, Article

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Citation Formats
A. C. Constantinou, B. Yet, N. Fenton, M. Neil, and W. Marsh, “Value of information analysis for interventional and counterfactual Bayesian networks in forensic medical sciences,” ARTIFICIAL INTELLIGENCE IN MEDICINE, pp. 41–52, 2016, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/56304.
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