کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
377577 658796 2016 12 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Value of information analysis for interventional and counterfactual Bayesian networks in forensic medical sciences
ترجمه فارسی عنوان
ارزش تجزیه و تحلیل اطلاعات برای شبکه های مداخله ای و مقابله با بی عدالتی در پزشکی قانونی
کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر هوش مصنوعی
چکیده انگلیسی


• A method based on the underlying principle of Value of Information analysis.
• For interventional and counterfactual Bayesian networks in forensic medical sciences.
• Examines whether interventional decision making is subject to amendments.
• Assesses what further information is worthwhile seeking prior to decision making.

ObjectivesInspired 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.MethodThe method is based on the underlying principle of Value of Information to enhance decision analysis in interventional and counterfactual Bayesian networks.ResultsThe method is applied to two real-world Bayesian network models (previously developed for decision support in forensic medical sciences) to examine the average gain in terms of both Value of Information (average relative gain ranging from 11.45% and 59.91%) and decision making (potential amendments in decision making ranging from 0% to 86.8%).ConclusionsWe have shown how the method becomes useful for decision makers, not only when decision making is subject to amendments on the basis of some unknown risk factors, but also when it is not. Knowing that a decision outcome is independent of one or more unknown risk factors saves us from the trouble of seeking information about the particular set of risk factors. Further, we have also extended the assessment of this implication to the counterfactual case and demonstrated how answers about interventional actions are expected to change when some unknown factors become known, and how useful this becomes in forensic medical science.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Artificial Intelligence in Medicine - Volume 66, January 2016, Pages 41–52
نویسندگان
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