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Value of information analysis for interventional and counterfactual Bayesian networks in forensic medical sciences
Date
2016-01-01
Author
Constantinou, Anthony Costa
Yet, Barbaros
Fenton, Norman
Neil, Martin
Marsh, William
Metadata
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Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License
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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.
Subject Keywords
Causal Inference
,
Bayesian Networks
,
Interventional Analysis
,
Counterfactual Analysis
,
Value Of Information
,
Forensic Medicine
URI
https://hdl.handle.net/11511/56304
Journal
ARTIFICIAL INTELLIGENCE IN MEDICINE
DOI
https://doi.org/10.1016/j.artmed.2015.09.002
Collections
Graduate School of Informatics, Article
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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.