Forensic scientists deal with the evaluation of a link between recovered ma- terial of unknown source found at a crime scene and control material coming from a suspect. The assessment of the value of the scientific evidence is typically performed by means of a likelihood ratio, a well established metric in forensic science. However, the derivation of a likelihood ratio may represent a demanding task with several sources of uncertainty, and this has originated a large debate about what should be the most appropriate way to take charge of such uncer- tainty while presenting expressions of evidential value at trial. In such a context, Bayesian networks represent a powerful tool that can be used to study, develop and implement probabilistic procedures for evaluating the probability value of the scientific evidence in forensic science or of an hypothesis of judicial interest.
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