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

Constantinou A. C., YET B., Fenton N., Neil M., Marsh W.

ARTIFICIAL INTELLIGENCE IN MEDICINE, cilt.66, ss.41-52, 2016 (SCI-Expanded, Scopus) identifier identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 66
  • Basım Tarihi: 2016
  • Doi Numarası: 10.1016/j.artmed.2015.09.002
  • Dergi Adı: ARTIFICIAL INTELLIGENCE IN MEDICINE
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.41-52
  • Anahtar Kelimeler: Causal inference, Bayesian networks, Interventional analysis, Counterfactual analysis, Value of Information, Forensic medicine, PARTIAL EXPECTED VALUE, CLINICAL-TRIAL DESIGN, SENSITIVITY-ANALYSIS, SAMPLE-SIZE, RISK
  • Orta Doğu Teknik Üniversitesi Adresli: Hayır

Özet

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.