title: A general approach to Bayesian networks for the interpretation of evidence.
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.
authors.affiliation: Institut de Police Scientifique et de Criminologie, The University of Lausanne, BCH, 1015, Lausanne-Dorigny, Switzerland. franco.taroni@esc.unil.ch
authors.forename: F
authors.initials: F
authors.lastname: Taroni
authors.forename: A
authors.initials: A
authors.lastname: Biedermann
authors.forename: P
authors.initials: P
authors.lastname: Garbolino
authors.forename: C G G
authors.initials: CG
authors.lastname: Aitken
mesh_terms: D001499:Bayes Theorem; D044707:Forensic Sciences / Q000379:methods* / Q000706:statistics & numerical data; D006801:Humans; D008962:Models, Theoretical