Hyoid bone-based sex discrimination among Egyptians using a multidetector computed tomography: discriminant function analysis, meta-analysis, and artificial intelligence-assisted study
Abstract The hyoid bone has been identified as sexually dimorphic in various populations. The current study is a forerunner analysis that used three-dimensional multidetector computed tomography (3D MDCT) images of the hyoid bone to examine sexual dimorphism in the Egyptian population. A total of 30...
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Nature Portfolio
2025-01-01
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| Series: | Scientific Reports |
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| Online Access: | https://doi.org/10.1038/s41598-025-85518-w |
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| author | Afaf Abdelkader Susan A. Ali Ahmed Abdeen Ehab S. Taher Asmaa Y. A. Hussein Mamdouh Eldesoqui Mohamed Abdo Liana Fericean Bănăţean-Dunea Ioan Samah F. Ibrahim Ashraf M. Said Darine Amin Elturabi E. Ebrahim Amany M. Allam Mihaela Ostan Khaled A. Bayoumi Tabinda Hasan Ekramy M. Elmorsy |
| author_facet | Afaf Abdelkader Susan A. Ali Ahmed Abdeen Ehab S. Taher Asmaa Y. A. Hussein Mamdouh Eldesoqui Mohamed Abdo Liana Fericean Bănăţean-Dunea Ioan Samah F. Ibrahim Ashraf M. Said Darine Amin Elturabi E. Ebrahim Amany M. Allam Mihaela Ostan Khaled A. Bayoumi Tabinda Hasan Ekramy M. Elmorsy |
| author_sort | Afaf Abdelkader |
| collection | DOAJ |
| description | Abstract The hyoid bone has been identified as sexually dimorphic in various populations. The current study is a forerunner analysis that used three-dimensional multidetector computed tomography (3D MDCT) images of the hyoid bone to examine sexual dimorphism in the Egyptian population. A total of 300 subjects underwent neck CT imaging, with an additional 60 subjects randomly selected for model validation. Ten hyoid variables were measured. Initially, the dataset was subjected to discriminant analysis to predict sex and the critical variables associated with sexual dimorphism. Subsequently, machine learning approaches were employed to enhance the accuracy of sex determination. The results indicated that all measured dimensions of the hyoid bone were substantially larger in males confront to females. Discriminant functions combining four measurements (major and minor axes of the hyoid body, the distance between the lesser horns, and hyoid bone length) achieved a higher accuracy of sex prediction compared to univariate functions. The accuracies of machine learning models ranged from 0.8667 to 0.933 with precision, recall, and F1-scores also showing improvements. These findings underscore the robustness and reliability of hyoid bone in sex discrimination among Egyptians, supported by both traditional statistical methods and machine learning approaches, and could prove invaluable in forensic cases. |
| format | Article |
| id | doaj-art-1ab52c60b9a743ffab8c521240b38f57 |
| institution | Kabale University |
| issn | 2045-2322 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj-art-1ab52c60b9a743ffab8c521240b38f572025-01-26T12:26:14ZengNature PortfolioScientific Reports2045-23222025-01-0115112010.1038/s41598-025-85518-wHyoid bone-based sex discrimination among Egyptians using a multidetector computed tomography: discriminant function analysis, meta-analysis, and artificial intelligence-assisted studyAfaf Abdelkader0Susan A. Ali1Ahmed Abdeen2Ehab S. Taher3Asmaa Y. A. Hussein4Mamdouh Eldesoqui5Mohamed Abdo6Liana Fericean7Bănăţean-Dunea Ioan8Samah F. Ibrahim9Ashraf M. Said10Darine Amin11Elturabi E. Ebrahim12Amany M. Allam13Mihaela Ostan14Khaled A. Bayoumi15Tabinda Hasan16Ekramy M. Elmorsy17Department of Forensic Medicine and Clinical Toxicology, Faculty of Medicine, Benha UniversityDepartment of Radiodiagnosis, Faculty of Medicine, Ain Shams UniversityDepartment of Forensic Medicine and Toxicology, Faculty of Veterinary Medicine, Benha UniversityDepartment of Basic and Clinical Medical Sciences, Faculty of Dentistry, Zarqa UniversityDepartment of Forensic Medicine and Clinical Toxicology, Faculty of Medicine, Benha UniversityDepartment of Basic Medical Sciences, College of Medicine, AlMaarefa UniversityDepartment of Animal Histology and Anatomy, School of Veterinary Medicine, Badr University in Cairo (BUC)Department of Biology and Plant Protection, Faculty of Agriculture, University of Life Sciences “King Michael I” from TimișoaraDepartment of Biology and Plant Protection, Faculty of Agriculture, University of Life Sciences “King Michael I” from TimișoaraDepartment of Internal Medicine, College of Medicine, Princess Nourah bint Abdulrahman UniversityBiomedical Engineering Program, Department of Electrical Engineering, Benha UniversityDepartment of Biological Anthropology, Medical Research and Clinical Studies Institute, National Research CenterDepartment of Medical-Surgical Nursing, College of Nursing, Prince Sattam bin Abdulaziz UniversityDepartment of Anatomy and Embryology, Faculty of Medicine, Benha UniversityDepartment of Biology, University of Life Sciences “King Michael I” from TimisoaraDepartment of Pathology, Faculty of Medicine, King Abdulaziz UniversityDepartment of Anatomy, College of Medicine, Princess Nourah bint Abdulrahman UniversityCenter for Health Research, Northern Border UniversityAbstract The hyoid bone has been identified as sexually dimorphic in various populations. The current study is a forerunner analysis that used three-dimensional multidetector computed tomography (3D MDCT) images of the hyoid bone to examine sexual dimorphism in the Egyptian population. A total of 300 subjects underwent neck CT imaging, with an additional 60 subjects randomly selected for model validation. Ten hyoid variables were measured. Initially, the dataset was subjected to discriminant analysis to predict sex and the critical variables associated with sexual dimorphism. Subsequently, machine learning approaches were employed to enhance the accuracy of sex determination. The results indicated that all measured dimensions of the hyoid bone were substantially larger in males confront to females. Discriminant functions combining four measurements (major and minor axes of the hyoid body, the distance between the lesser horns, and hyoid bone length) achieved a higher accuracy of sex prediction compared to univariate functions. The accuracies of machine learning models ranged from 0.8667 to 0.933 with precision, recall, and F1-scores also showing improvements. These findings underscore the robustness and reliability of hyoid bone in sex discrimination among Egyptians, supported by both traditional statistical methods and machine learning approaches, and could prove invaluable in forensic cases.https://doi.org/10.1038/s41598-025-85518-wEgyptian populationForensic anthropologySex discriminationHyoid boneMeta-analysisMultidetector computed tomography |
| spellingShingle | Afaf Abdelkader Susan A. Ali Ahmed Abdeen Ehab S. Taher Asmaa Y. A. Hussein Mamdouh Eldesoqui Mohamed Abdo Liana Fericean Bănăţean-Dunea Ioan Samah F. Ibrahim Ashraf M. Said Darine Amin Elturabi E. Ebrahim Amany M. Allam Mihaela Ostan Khaled A. Bayoumi Tabinda Hasan Ekramy M. Elmorsy Hyoid bone-based sex discrimination among Egyptians using a multidetector computed tomography: discriminant function analysis, meta-analysis, and artificial intelligence-assisted study Scientific Reports Egyptian population Forensic anthropology Sex discrimination Hyoid bone Meta-analysis Multidetector computed tomography |
| title | Hyoid bone-based sex discrimination among Egyptians using a multidetector computed tomography: discriminant function analysis, meta-analysis, and artificial intelligence-assisted study |
| title_full | Hyoid bone-based sex discrimination among Egyptians using a multidetector computed tomography: discriminant function analysis, meta-analysis, and artificial intelligence-assisted study |
| title_fullStr | Hyoid bone-based sex discrimination among Egyptians using a multidetector computed tomography: discriminant function analysis, meta-analysis, and artificial intelligence-assisted study |
| title_full_unstemmed | Hyoid bone-based sex discrimination among Egyptians using a multidetector computed tomography: discriminant function analysis, meta-analysis, and artificial intelligence-assisted study |
| title_short | Hyoid bone-based sex discrimination among Egyptians using a multidetector computed tomography: discriminant function analysis, meta-analysis, and artificial intelligence-assisted study |
| title_sort | hyoid bone based sex discrimination among egyptians using a multidetector computed tomography discriminant function analysis meta analysis and artificial intelligence assisted study |
| topic | Egyptian population Forensic anthropology Sex discrimination Hyoid bone Meta-analysis Multidetector computed tomography |
| url | https://doi.org/10.1038/s41598-025-85518-w |
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