Use of Bayesian Networks for the investigation of the nature of biological material in casework.

Détails

Ressource 1Télécharger: 2022_BN biological fluids.pdf (2600.14 [Ko])
Etat: Public
Version: Final published version
Licence: CC BY 4.0
ID Serval
serval:BIB_2E76CAA88C08
Type
Article: article d'un périodique ou d'un magazine.
Collection
Publications
Institution
Titre
Use of Bayesian Networks for the investigation of the nature of biological material in casework.
Périodique
Forensic science international
Auteur⸱e⸱s
Samie L., Champod C., Delémont S., Basset P., Hicks T., Castella V.
ISSN
1872-6283 (Electronic)
ISSN-L
0379-0738
Statut éditorial
Publié
Date de publication
02/2022
Peer-reviewed
Oui
Volume
331
Pages
111174
Langue
anglais
Notes
Publication types: Journal Article
Publication Status: ppublish
Résumé
Chemical and staining methods, immunochromatography, spectroscopy, RNA expression or methylation patterns, do not allow to determine the nature of the biological material with certainty. However, to our knowledge, there are few forensic scientists that assess the value of such test results using a probabilistic approach. This is surprising as it would allow account for false positives and false negatives and avoid misleading conclusions. In this paper, we developed three Bayesian Networks (BNs) to assess the presence of blood, saliva and sperm in the recovered material and combine potentially contradictory observations. The approach was successfully tested using 188 traces from proficiency tests. We have implemented an online user-friendly application (https://forensic-genetic.shinyapps.io/BodyFluidsApp/) that allows forensic scientists to assess the value of their results without having to build Bayesian Networks themselves. They can also input their own data, use the application to identify a potential lack of knowledge and report their conclusions regarding the presence of sperm, blood or/and saliva considering uncertainty.
Mots-clé
Bayes Theorem, Forensic Medicine, Saliva, Body Fluid detection, Christmas Tree staining, Likelihood ratio, OBTI, PSA, RSID Saliva
Pubmed
Web of science
Open Access
Oui
Création de la notice
10/01/2022 9:27
Dernière modification de la notice
21/11/2022 8:23
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