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Updated: Aug 29, 2026

Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems
Published on: June 13, 2025
A general approach to Bayesian networks for the interpretation of evidence
F Taroni1, A Biedermann, P Garbolino
1Institut de Police Scientifique et de Criminologie, The University of Lausanne, BCH, 1015, Lausanne-Dorigny, Switzerland. franco.taroni@esc.unil.ch
Abstract:
Bayesian networks (BNs) are mathematically and statistically rigorous techniques for handling uncertainty. The field of forensic science has recently attributed increased attention to the many advantages of this graphical method for assisting the evaluation of scientific evidence. However, the majority of contributions that relate to this topic restrict themselves to the presentation of already "constructed" BNs, and often, only a few explanations are given as to how one obtains a specific BN structure for a given problem. Based on several examples, the present paper will therefore attempt to explain in more detail some guiding considerations that might be helpful for the elicitation of appropriate structures for BNs.
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