Artificial intelligence methods for a Bayesian epistemology-powered evidence evaluation.

Journal: Journal of evaluation in clinical practice
Published Date: Feb 11, 2021

Abstract

RATIONALE, AIMS AND OBJECTIVES: The diversity of types of evidence (eg, case reports, animal studies and observational studies) makes the assessment of a drug's safety profile into a formidable challenge. While frequentist uncertain inference struggles in aggregating these signals, the more flexible Bayesian approaches seem better suited for this quest. Artificial Intelligence (AI) offers great promise to these approaches for information retrieval, decision support, and learning probabilities from data.

Authors

  • Francesco De Pretis
    Department of Biomedical Sciences and Public Health, School of Medicine and Surgery, Marche Polytechnic University, Ancona, Italy.
  • Jürgen Landes
    Munich Center for Mathematical Philosophy, Faculty of Philosophy, Philosophy of Science and Study of Religion, Ludwig-Maximilians-Universität München, Munich, Germany.
  • William Peden
    Erasmus Institute for Philosophy and Economics, Erasmus School of Philosophy, Erasmus University Rotterdam, Rotterdam, The Netherlands.

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