Hamdan, Sharifah Nabilah Syed Mohd and Rahmat, Rabiah Al-Adawiyah and Razak, Fathilah Abdul and Kadir, Khairul Azmi Abd and Abdullah, Erma Rahayu Mohd Faizal and Ibrahim, Norliza (2023) Sex estimation of Malaysian sub-adults using craniometrics: A computed tomography study. Legal Medicine, 64. ISSN 1344-6223, DOI https://doi.org/10.1016/j.legalmed.2023.102275.
Full text not available from this repository.Abstract
Sex estimation is crucial in biological profiling of skeletal human remains. Methods used for sex estimation in adults are less effective for sub-adults due to varied cranium patterns during the growth period. Hence, this study aimed to develop a sex estimation model for Malaysian sub-adults using craniometric measurements obtained through multi-slice computed tomography (MSCT). A total of 521 cranial MSCT dataset of sub-adult Malaysians (279 males, 242 females; 0-20 years old) were collected. Mimics software version 21.0 (Materialise, Leuven, Belgium) was used to construct three-dimensional (3D) models. A plane-to-plane (PTP) protocol was utilised to measure 14 selected craniometric parameters. Discriminant function analysis (DFA) and binary logistic regression (BLR) were used to statistically analyze the data. In this study, low level of sexual dimorphism was observed in cranium below 6 years old. The level was then increased with age. For sample validation data, the accuracy of DFA and BLR in estimating sex improved with age from 61.6% to 90.3%. All age groups except 0-2 and 3-6 showed high accuracy percentage (>= 75%) when tested using DFA and BLR. DFA and BLR can be utilised to estimate sex for Malaysian sub-adult using MSCT craniometric measurements. However, BLR showed higher accuracy than DFA in sex estimation of sub-adults.
| Item Type: | Article |
|---|---|
| Funders: | Universiti Malaya (RMF 0637-2021) |
| Uncontrolled Keywords: | Forensic anthropology; Sex estimation; Cranium; Computed tomography; Discriminant function analysis; Binary logistic regression |
| Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science R Medicine > R Medicine (General) R Medicine > RK Dentistry |
| Divisions: | Faculty of Computer Science & Information Technology > Department of Artificial Intelligence Faculty of Dentistry > Department of Oral & Craniofacial Sciences Faculty of Dentistry > Department of Oral & Maxillofacial Clinical Sciences Faculty of Medicine > Biomedical Imaging Department |
| Depositing User: | Ms. Juhaida Abd Rahim |
| Date Deposited: | 01 Oct 2025 02:48 |
| Last Modified: | 01 Oct 2025 02:49 |
| URI: | http://eprints.um.edu.my/id/eprint/50301 |
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