{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,9]],"date-time":"2026-09-09T18:45:03Z","timestamp":1788979503715,"version":"build-2803163510"},"reference-count":22,"publisher":"Public Library of Science (PLoS)","issue":"11","license":[{"start":{"date-parts":[[2024,11,15]],"date-time":"2024-11-15T00:00:00Z","timestamp":1731628800000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["www.plosone.org"],"crossmark-restriction":false},"short-container-title":["PLoS ONE"],"abstract":"<jats:p>Characteristics of the mandible structures have been relevant in anthropological and forensic studies for sex prediction. This study aims to evaluate the coronoid process, condyle, and sigmoid notch patterns in sex prediction through supervised machine learning algorithms. Cephalometric radiographs from 410 dental records of patients were screened to investigate the morphology of the coronoid process, condyle, and sigmoid notch and the Co-Gn distance. The following machine learning algorithms were used to build the predictive models: Decision Tree, Gradient Boosting Classifier, K-Nearest Neighbors (KNN), Logistic Regression, Multilayer Perceptron Classifier, Random Forest Classifier, and Support Vector Machine (SVM). A 5-fold cross-validation approach was adopted to validate each model. Metrics such as area under the curve (AUC), accuracy, recall, precision, and F1 Score were calculated for each model, and ROC curves were constructed. All tested variables demonstrated statistical significance (p &lt; 0.10) and were included in the construction of the predictive model. The Co-Gn variable stood out as the most important among the evaluated independent variables, showing greater relevance in three of the four algorithms used in assessing feature importance. In the analysis of the models\u2019 performance, the AUC ranged from 0.82 [95% CI = 0.72\u20130.93] to 0.66 [95% CI = 0.53\u20130.76] for the test data, and from 0.83 [95% CI = 0.80\u20130.87] to 0.71 [95% CI = 0.61\u20130.75] for cross-validation. The precision of the models ranged from 0.83 [95% CI = 0.75\u20130.91] to 0.68 [95% CI = 0.58\u20130.78] in the test phase, and from 0.78 [95% CI = 0.74\u20130.82] to 0.69 [95% CI = 0.65\u20130.75] in cross-validation. The SVM, KNN, and Gradient Boosting Classifier algorithms stood out with the highest AUC and precision values in both cross-validation and testing. The use of condyle, coronoid process, and sigmoid notch characteristics, in combination with supervised machine learning predictive models, shows potential for contributing to sex prediction based on morphometric bone characteristics, particularly regarding the distance between the condyle and gnathion. However, given the study\u2019s limitations, these findings should be interpreted with caution.<\/jats:p>","DOI":"10.1371\/journal.pone.0312824","type":"journal-article","created":{"date-parts":[[2024,11,15]],"date-time":"2024-11-15T13:34:35Z","timestamp":1731677675000},"page":"e0312824","update-policy":"https:\/\/doi.org\/10.1371\/journal.pone.corrections_policy","source":"Crossref","is-referenced-by-count":16,"title":["Sex prediction through machine learning utilizing mandibular condyles, coronoid processes, and sigmoid notches features"],"prefix":"10.1371","volume":"19","author":[{"given":"Isabela Bittencourt","family":"Basso","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Pedro Felipe","family":"de Jesus Freitas","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Aline Xavier","family":"Ferraz","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ana Julia","family":"Borkovski","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ana Laura","family":"Borkovski","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Rosane Sampaio","family":"Santos","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Rodrigo Nunes","family":"Rached","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Erika Calvano","family":"K\u00fcchler","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Angela Graciela Deliga","family":"Schroder","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1325-4248","authenticated-orcid":true,"given":"Cristiano Miranda","family":"de Araujo","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9799-1223","authenticated-orcid":true,"given":"Odilon","family":"Guariza-Filho","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"340","published-online":{"date-parts":[[2024,11,15]]},"reference":[{"key":"pone.0312824.ref001","doi-asserted-by":"crossref","first-page":"5","DOI":"10.1016\/j.job.2023.11.006","article-title":"Biological profiling using the human mandible","volume":"66","author":"D Abualhija","year":"2024","journal-title":"Journal of oral biosciences"},{"key":"pone.0312824.ref002","first-page":"53","article-title":"Role of mandibular anatomical structures in sexual dimorphism in Turkish population: a radiomorphometric CBCT study","volume":"40","author":"GB Senol","year":"2022","journal-title":"J Forensic Odontostomatol"},{"key":"pone.0312824.ref003","doi-asserted-by":"crossref","first-page":"44","DOI":"10.1186\/s13005-024-00446-w","article-title":"Sex determination through maxillary dental arch and skeletal base measurements using machine learning","volume":"20","author":"CM de Araujo","year":"2024","journal-title":"Head & face medicine"},{"key":"pone.0312824.ref004","doi-asserted-by":"crossref","first-page":"65","DOI":"10.33314\/jnhrc.v20i01.3822","article-title":"Morphometric Analysis of Mandibular Ramus for Sex Determination on Orthopantomogram","volume":"20","author":"T Shakya","year":"2022","journal-title":"J Nepal Health Res Counc"},{"key":"pone.0312824.ref005","doi-asserted-by":"crossref","first-page":"25","DOI":"10.25259\/JCIS_27_2022","article-title":"Morphometric anlaysis of mandibular coronoid, condyle and sigmoid shape using panoromic view for personal identification in south Indian population","volume":"12","author":"M Manoj","year":"2022","journal-title":"J Clin Imaging Sci"},{"key":"pone.0312824.ref006","first-page":"e40275","article-title":"Assessment of Morphological Variations of the Coronoid Process, Condyle, and Sigmoid Notch as an Adjunct in Personal Identification Using Orthopantomograms Among the North Indian Population","volume":"15","author":"SK Bains","year":"2023","journal-title":"Cureus"},{"key":"pone.0312824.ref007","article-title":"Reveal the concealed \u2010 morphological variations of the coronoid process, condyle and sigmoid notch in personal identification","author":"RS Sahithi D","year":"2016","journal-title":"Egypt J Forensic Sci"},{"key":"pone.0312824.ref008","doi-asserted-by":"crossref","first-page":"101826","DOI":"10.1016\/j.legalmed.2020.101826","article-title":"Application and performance of artificial intelligence technology in forensic odontology \u2010 A systematic review","volume":"48","author":"SB Khanagar","year":"2021","journal-title":"Leg Med (Tokyo)"},{"key":"pone.0312824.ref009","article-title":"The Accuracy of Sex Identification Using CBCT Morphometric Measurements of the Mandible, with Different Machine-Learning Algorithms-A Retrospective Study","volume":"13","author":"MTA Baban","year":"2023","journal-title":"Diagnostics (Basel, Switzerland)"},{"key":"pone.0312824.ref010","first-page":"415","article-title":"Comparison of mandibular morphometric parameters in digital panoramic radiography in gender determination using machine learning","volume":"40","author":"H Pertek","year":"2024","journal-title":"Oral"},{"key":"pone.0312824.ref011","doi-asserted-by":"crossref","first-page":"9587","DOI":"10.1038\/s41598-024-59556-9","article-title":"Mandibular and dental measurements for sex determination using machine learning","volume":"14","author":"EC K\u00fcchler","year":"2024","journal-title":"Scientific Reports"},{"key":"pone.0312824.ref012","doi-asserted-by":"crossref","first-page":"732","DOI":"10.4103\/njcp.njcp_787_23","article-title":"Gender Estimation from Morphometric Measurements of Mandibular Lingula by Using Machine Learning Algorithms and Artificial Neural Networks","volume":"27","author":"D \u015eenol","year":"2024","journal-title":"Nigerian journal of clinical practice"},{"key":"pone.0312824.ref013","first-page":"e40434","article-title":"Anatomical Variants of Condylar Process, Coronoid Process, and Sigmoid Notch in a Maharashtrian Population: A Radiographic Study","volume":"15","author":"S Mahapatra","year":"2023","journal-title":"Cureus"},{"key":"pone.0312824.ref014","first-page":"8948082","article-title":"Stacking Ensemble Method for Gestational Diabetes Mellitus Prediction in Chinese Pregnant Women: A Prospective Cohort Study","volume":"2022","author":"R Liu","year":"2022","journal-title":"Journal of healthcare engineering"},{"key":"pone.0312824.ref015","doi-asserted-by":"crossref","DOI":"10.3390\/ijerph18031023","article-title":"Identification Framework of Contaminant Spill in Rivers Using Machine Learning with Breakthrough Curve Analysis","volume":"18","author":"S Kwon","year":"2021","journal-title":"International journal of environmental research and public health"},{"key":"pone.0312824.ref016","doi-asserted-by":"crossref","unstructured":"Nitesh VC and Kevin WB LOKW (2002). Smote: synthetic minority over-sampling technique. Journal of Artificial Intelligence Research:321\u2013357.","DOI":"10.1613\/jair.953"},{"key":"pone.0312824.ref017","doi-asserted-by":"crossref","first-page":"101771","DOI":"10.1016\/j.legalmed.2020.101771","article-title":"On the use of machine learning algorithms in forensic anthropology","volume":"47","author":"E Nikita","year":"2020","journal-title":"Legal Medicine"},{"key":"pone.0312824.ref018","doi-asserted-by":"crossref","first-page":"1887","DOI":"10.1007\/s00414-023-03072-4","article-title":"Sex estimation from long bones: a machine learning approach","volume":"137","author":"S Knecht","year":"2023","journal-title":"International Journal of Legal Medicine"},{"key":"pone.0312824.ref019","doi-asserted-by":"crossref","first-page":"414","DOI":"10.4103\/jomfp.jomfp_74_22","article-title":"Assessment of condyle-coronoid angle and gonial angle for gender determination: A digital panoramic study in Bagalkot population","volume":"26","author":"P Ingaleshwar","year":"2022","journal-title":"J Oral Maxillofac Pathol"},{"key":"pone.0312824.ref020","doi-asserted-by":"crossref","first-page":"110623","DOI":"10.1016\/j.jbiomech.2021.110623","article-title":"Sexual dimorphisms in three-dimensional masticatory muscle attachment morphometry regulates temporomandibular joint mechanics","volume":"126","author":"X She","year":"2021","journal-title":"Journal of biomechanics"},{"key":"pone.0312824.ref021","doi-asserted-by":"crossref","first-page":"24039","DOI":"10.1038\/s41598-021-03430-5","article-title":"Research on expansion and classification of imbalanced data based on SMOTE algorithm","volume":"11","author":"S Wang","year":"2021","journal-title":"Scientific Reports"},{"key":"pone.0312824.ref022","doi-asserted-by":"crossref","first-page":"32","DOI":"10.1016\/j.ins.2019.07.070","article-title":"A Comprehensive Analysis of Synthetic Minority Oversampling Technique (SMOTE) for handling class imbalance","volume":"505","author":"D Elreedy","year":"2019","journal-title":"Information Sciences"}],"container-title":["PLOS ONE"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/dx.plos.org\/10.1371\/journal.pone.0312824","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,12,1]],"date-time":"2024-12-01T06:16:57Z","timestamp":1733033817000},"score":1,"resource":{"primary":{"URL":"https:\/\/dx.plos.org\/10.1371\/journal.pone.0312824"}},"subtitle":[],"editor":[{"given":"Giulia","family":"Pascoletti","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"editor"}]}],"short-title":[],"issued":{"date-parts":[[2024,11,15]]},"references-count":22,"journal-issue":{"issue":"11","published-online":{"date-parts":[[2024,11,15]]}},"URL":"https:\/\/doi.org\/10.1371\/journal.pone.0312824","relation":{},"ISSN":["1932-6203"],"issn-type":[{"value":"1932-6203","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,11,15]]}}}