Sex estimation from the first and second ribs using 3D postmortem CT images in a Japanese population: A comparison of discriminant analysis and machine learning techniques
This study investigated the use of 3D postmortem computed tomography (PMCT) images of the first and second ribs for sex estimation in a Japanese population. Sex estimation models using conventional discriminant analysis and ten machine learning algorithms including logistic regression (LR), Naive Ba...
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| Format: | Article |
| Language: | English |
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Elsevier
2024-12-01
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| Series: | Forensic Science International: Reports |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2665910724000355 |
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| author | Tawachai Monum Yohsuke Makino Daisuke Yajima Go Inoguchi Fumiko Chiba Suguru Torimitsu Maiko Yoshida Patison Palee Yumi Hoshioka Naoki Saito Hirotaro Iwase |
| author_facet | Tawachai Monum Yohsuke Makino Daisuke Yajima Go Inoguchi Fumiko Chiba Suguru Torimitsu Maiko Yoshida Patison Palee Yumi Hoshioka Naoki Saito Hirotaro Iwase |
| author_sort | Tawachai Monum |
| collection | DOAJ |
| description | This study investigated the use of 3D postmortem computed tomography (PMCT) images of the first and second ribs for sex estimation in a Japanese population. Sex estimation models using conventional discriminant analysis and ten machine learning algorithms including logistic regression (LR), Naive Bayes (NB), K-Nearest Neighbors (KNN), decision tree (DT), random forest (RF), support vector machine (SVM), linear discriminant analysis (LDA), quadratic discriminant analysis (QDA), artificial neural network (ANN), and extra tree (ET), were achieved from PMCT measurements of the first and second rib and the accuracy of models were compared. The results showed that ML algorithms, particularly LR, outperformed discriminant analysis, achieving an accuracy of 83.6 % compared to 79.1 % for stepwise discriminant analysis. This study highlights the potential of 3D PMCT and ML for accurate sex estimation in forensic anthropology. |
| format | Article |
| id | doaj-art-d733bf046b3e46da8e65a28c25b05a8c |
| institution | Kabale University |
| issn | 2665-9107 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Forensic Science International: Reports |
| spelling | doaj-art-d733bf046b3e46da8e65a28c25b05a8c2024-12-19T11:00:29ZengElsevierForensic Science International: Reports2665-91072024-12-0110100386Sex estimation from the first and second ribs using 3D postmortem CT images in a Japanese population: A comparison of discriminant analysis and machine learning techniquesTawachai Monum0Yohsuke Makino1Daisuke Yajima2Go Inoguchi3Fumiko Chiba4Suguru Torimitsu5Maiko Yoshida6Patison Palee7Yumi Hoshioka8Naoki Saito9Hirotaro Iwase10Department of Forensic Medicine, Faculty of Medicine, Chiang Mai University, 110, Intravaroros Rd, Sriphoom, Muang, Chiang 50200, Thailand; Department of Legal Medicine, Graduate School of Medicine, Chiba University, 1-8-1 Inohana, Chuo-ku, Chiba 260-8670, Japan; Corresponding author at: Department of Forensic Medicine, Faculty of Medicine, Chiang Mai University, 110, Intravaroros Rd, Sriphoom, Muang, Chiang 50200, Thailand.Department of Legal Medicine, Graduate School of Medicine, Chiba University, 1-8-1 Inohana, Chuo-ku, Chiba 260-8670, Japan; Department of Forensic Medicine, Graduate School of Medicine, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, JapanDepartment of Legal Medicine, Graduate School of Medicine, Chiba University, 1-8-1 Inohana, Chuo-ku, Chiba 260-8670, Japan; Department of Forensic Medicine, School of Medicine, International University of Health and Welfare, 4-3, Kozunomori, Narita-city, Chiba 286-8686, JapanDepartment of Legal Medicine, Graduate School of Medicine, Chiba University, 1-8-1 Inohana, Chuo-ku, Chiba 260-8670, JapanDepartment of Legal Medicine, Graduate School of Medicine, Chiba University, 1-8-1 Inohana, Chuo-ku, Chiba 260-8670, JapanDepartment of Legal Medicine, Graduate School of Medicine, Chiba University, 1-8-1 Inohana, Chuo-ku, Chiba 260-8670, Japan; Department of Forensic Medicine, Graduate School of Medicine, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, JapanDepartment of Legal Medicine, Graduate School of Medicine, Chiba University, 1-8-1 Inohana, Chuo-ku, Chiba 260-8670, JapanCollege of Arts, Media and Technology, Chiang Mai University, Chiang Mai 50200, ThailandDepartment of Legal Medicine, Graduate School of Medicine, Chiba University, 1-8-1 Inohana, Chuo-ku, Chiba 260-8670, JapanDepartment of Legal Medicine, Graduate School of Medicine, Chiba University, 1-8-1 Inohana, Chuo-ku, Chiba 260-8670, JapanDepartment of Legal Medicine, Graduate School of Medicine, Chiba University, 1-8-1 Inohana, Chuo-ku, Chiba 260-8670, JapanThis study investigated the use of 3D postmortem computed tomography (PMCT) images of the first and second ribs for sex estimation in a Japanese population. Sex estimation models using conventional discriminant analysis and ten machine learning algorithms including logistic regression (LR), Naive Bayes (NB), K-Nearest Neighbors (KNN), decision tree (DT), random forest (RF), support vector machine (SVM), linear discriminant analysis (LDA), quadratic discriminant analysis (QDA), artificial neural network (ANN), and extra tree (ET), were achieved from PMCT measurements of the first and second rib and the accuracy of models were compared. The results showed that ML algorithms, particularly LR, outperformed discriminant analysis, achieving an accuracy of 83.6 % compared to 79.1 % for stepwise discriminant analysis. This study highlights the potential of 3D PMCT and ML for accurate sex estimation in forensic anthropology.http://www.sciencedirect.com/science/article/pii/S2665910724000355Sex estimationFirst ribSecond ribPMCTJapanese populationMachine learning |
| spellingShingle | Tawachai Monum Yohsuke Makino Daisuke Yajima Go Inoguchi Fumiko Chiba Suguru Torimitsu Maiko Yoshida Patison Palee Yumi Hoshioka Naoki Saito Hirotaro Iwase Sex estimation from the first and second ribs using 3D postmortem CT images in a Japanese population: A comparison of discriminant analysis and machine learning techniques Forensic Science International: Reports Sex estimation First rib Second rib PMCT Japanese population Machine learning |
| title | Sex estimation from the first and second ribs using 3D postmortem CT images in a Japanese population: A comparison of discriminant analysis and machine learning techniques |
| title_full | Sex estimation from the first and second ribs using 3D postmortem CT images in a Japanese population: A comparison of discriminant analysis and machine learning techniques |
| title_fullStr | Sex estimation from the first and second ribs using 3D postmortem CT images in a Japanese population: A comparison of discriminant analysis and machine learning techniques |
| title_full_unstemmed | Sex estimation from the first and second ribs using 3D postmortem CT images in a Japanese population: A comparison of discriminant analysis and machine learning techniques |
| title_short | Sex estimation from the first and second ribs using 3D postmortem CT images in a Japanese population: A comparison of discriminant analysis and machine learning techniques |
| title_sort | sex estimation from the first and second ribs using 3d postmortem ct images in a japanese population a comparison of discriminant analysis and machine learning techniques |
| topic | Sex estimation First rib Second rib PMCT Japanese population Machine learning |
| url | http://www.sciencedirect.com/science/article/pii/S2665910724000355 |
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