{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,8]],"date-time":"2026-09-08T14:10:52Z","timestamp":1788876652007,"version":"build-2803163510"},"reference-count":30,"publisher":"MDPI AG","issue":"18","license":[{"start":{"date-parts":[[2026,9,8]],"date-time":"2026-09-08T00:00:00Z","timestamp":1788825600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Diagnostics"],"abstract":"<jats:p>Background\/Objectives: Sex estimation is a fundamental component of the forensic biological profile, and the pelvis is widely regarded as the most sexually dimorphic skeletal element. This study aimed to quantify pelvic sexual dimorphism in a contemporary Turkish sample using computed tomography (CT)-derived morphometric measurements, and to evaluate the performance of several machine learning (ML) algorithms for sex classification. Methods: Fourteen pelvic measurements were obtained from CT reconstructions of 201 individuals (101 males, 100 females) by a single observer; a stratified subset of 30 cases (15 males, 15 females) was remeasured by the same observer and by a second observer to assess intra- and inter-observer reliability. Four supervised ML classifiers\u2014logistic regression, linear discriminant analysis (LDA), random forest, and support vector machine (SVM)\u2014were trained and evaluated using stratified 10-fold cross-validation and an independent 30% hold-out test set. Results: Thirteen of the fourteen measurements differed significantly between sexes (p &lt; 0.05). Intra-observer reliability was excellent for all 14 measurements (ICC = 0.943\u20130.998), and inter-observer reliability was good to excellent (ICC = 0.834\u20130.996), with the lowest value observed for pubic length. Cross-validated classification accuracy ranged from 98.0% (random forest) to 99.0% (logistic regression, LDA, and SVM), with corresponding cross-validated AUC values of 0.991\u20130.994, with logistic regression, LDA, and SVM each achieving 100% accuracy (AUC = 1.000) on the independent hold-out set (random forest: 96.7%, AUC = 0.999). Acetabular width was identified as the single most informative predictor (univariate area under the curve = 0.972), followed by acetabular height, the subpubic angle, ischial length, the transverse pelvic outlet, and the angle of the greater sciatic notch. Conclusions: These findings demonstrate that CT-derived pelvic morphometrics, combined with machine learning classification, provide a highly accurate and reproducible method for sex estimation in a Turkish forensic context, and support the development of population-specific standards for forensic anthropological casework, pending independent external validation; the classification and effect-size estimates reported here were, however, stable under repeated cross-validation and hyperparameter optimisation.<\/jats:p>","DOI":"10.3390\/diagnostics16182893","type":"journal-article","created":{"date-parts":[[2026,9,8]],"date-time":"2026-09-08T13:46:33Z","timestamp":1788875193000},"page":"2893","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Machine Learning-Based Sex Estimation from Computed Tomography-Derived Pelvic Morphometric Measurements in a Contemporary Turkish Population"],"prefix":"10.3390","volume":"16","author":[{"given":"Gokce","family":"Karaman","sequence":"first","affiliation":[{"name":"Faculty of Medicine, Department of Forensic Medicine, University of Dokuz Eylul, 35100 Izmir,  T\u00fcrkiye"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3708-1214","authenticated-orcid":false,"given":"Ali","family":"Er","sequence":"additional","affiliation":[{"name":"Tepecik Training and Research Hospital, University of Health Sciences, 35180 Izmir, T\u00fcrkiye"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mustafa","family":"Bozdag","sequence":"additional","affiliation":[{"name":"Tepecik Training and Research Hospital, University of Health Sciences, 35180 Izmir, T\u00fcrkiye"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Manon","family":"Hache","sequence":"additional","affiliation":[{"name":"Department of Forensic Medicine, CHU Dijon-Bourgogne, 21000 Dijon, France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0007-8350-3904","authenticated-orcid":false,"given":"Siam","family":"Knecht","sequence":"additional","affiliation":[{"name":"CNRS, EFS, ADES, Aix Marseille University,  13344 Marseille, France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6948-120X","authenticated-orcid":false,"given":"Sophie","family":"Colomb","sequence":"additional","affiliation":[{"name":"L\u2019\u00c9quipe de Droit P\u00e9nal et de Sciences Forensiques de Montpellier (EDPFM), University of Montpellier, 34000 Montpellier, France"},{"name":"Department of Legal Medicine, CHU Montpellier, University of Montpellier, 34000 Montpellier, France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7390-8947","authenticated-orcid":false,"given":"Laurent","family":"Martrille","sequence":"additional","affiliation":[{"name":"CNRS, EFS, ADES, Aix Marseille University,  13344 Marseille, France"},{"name":"Department of Legal Medicine, CHU Montpellier, University of Montpellier, 34000 Montpellier, France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5101-9508","authenticated-orcid":false,"given":"Pascal","family":"Adalian","sequence":"additional","affiliation":[{"name":"CNRS, EFS, ADES, Aix Marseille University,  13344 Marseille, France"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2026,9,8]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"861","DOI":"10.1007\/s00414-014-0999-8","article-title":"Morphometric analysis of pelvic sexual dimorphism in a contemporary Western Australian population","volume":"128","author":"Franklin","year":"2014","journal-title":"Int. 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