Interpretable machine learning models for predicting incestuous relationships from short tandem repeat profiles in sexual assault-related pregnancies for forensic intelligence.

Saved in:
Bibliographic Details
Title: Interpretable machine learning models for predicting incestuous relationships from short tandem repeat profiles in sexual assault-related pregnancies for forensic intelligence.
Authors: Inokuchi S; Department of Forensic Medicine, Graduate School of Medicine, Juntendo University, 2-1-1 Hongo, Bunkyo-ku, Tokyo, Japan; Forensic Science Laboratory, Tokyo Metropolitan Police Department, 3-35-21 Shakujiidai, Nerima-ku, Tokyo, Japan. Electronic address: s-inoku@juntendo.ac.jp., Satoh T; Forensic Science Laboratory, Kumamoto Prefectural Police Headquarters, 6-18-1 Suizenji, Chuo-ku, Kumamoto, Japan., Nakanishi H; Department of Forensic Medicine, Graduate School of Medicine, Juntendo University, 2-1-1 Hongo, Bunkyo-ku, Tokyo, Japan; Department of Forensic Medicine, Saitama Medical University, 38 Moroyamamachimorohongo, Saitama, Japan., Takada A; Department of Forensic Medicine, Graduate School of Medicine, Juntendo University, 2-1-1 Hongo, Bunkyo-ku, Tokyo, Japan; Department of Forensic Medicine, Saitama Medical University, 38 Moroyamamachimorohongo, Saitama, Japan., Saito K; Department of Forensic Medicine, Graduate School of Medicine, Juntendo University, 2-1-1 Hongo, Bunkyo-ku, Tokyo, Japan; Department of Forensic Medicine, Saitama Medical University, 38 Moroyamamachimorohongo, Saitama, Japan.
Source: Legal medicine (Tokyo, Japan) [Leg Med (Tokyo)] 2026 Jul; Vol. 84, pp. 102889. Date of Electronic Publication: 2026 Jun 09.
Publication Type: Journal Article
Journal Info: Publisher: Elsevier Science Ireland Ltd Country of Publication: Ireland NLM ID: 100889186 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1873-4162 (Electronic) Linking ISSN: 13446223 NLM ISO Abbreviation: Leg Med (Tokyo) Subsets: MEDLINE
Database: MEDLINE Ultimate
Description
ISSN:1873-4162
DOI:10.1016/j.legalmed.2026.102889