Integrating artificial intelligence and adult dental age estimation in forensic identification: A literature review
1 Department of Forensic Odontology, Faculty of Dental Medicine, Universitas Airlangga, Surabaya, Indonesia
2 Magister of Dental Health Sciences, Faculty of Dental Medicine, Universitas Airlangga, Surabaya, Indonesia.
Review Article
World Journal of Advanced Research and Reviews, 2024, 21(02), 1374–1379
Article DOI: 10.30574/wjarr.2024.21.2.0605
Publication history:
Received on 13 January 2024; revised on 20 February 2024; accepted on 22 February 2024
Abstract:
Age estimation is crucial in various forensic fields, including forensic medicine, anthropology, and demographic studies. Adult dental age estimation is affected by multiple factors, resulting in discrepancies between dental age and chronological age. The development of artificial intelligence (AI) technology has led to extensive investigations in forensic sciences, encompassing several areas such as facial recognition, age, sex identification, and DNA analysis. Adult age estimation methods commonly used include the pulp-tooth ratio approach, the Harris & Nortje method, and the Van Heerden method. AI approaches such as Fuzzy Logic (FL), Evolutionary Computing (EC), and Machine Learning (ML) are being extensively applied. These techniques use algorithms to imitate human thinking and behavior. Deep learning techniques, explicitly using deep convolutional neural networks (DCNN), enable age estimation by segmenting images and making measurements, replicating the cognitive processes of radiologists when computing indices such as the third molar maturity (I3M) index. Also, DCNNs automatically optimize teeth segmentation in dental X-ray images, improving image refining and analysis efficiency. AI integration in forensic dentistry improves the precision and effectiveness of dental data processing while significantly accelerating individual identification procedures. Incorporating this technology shows potential for enhancing the caliber and dependability of evidence in forensic investigations.
Keywords:
Artificial intelligence; Dental age estimation; Forensic dentistry; Human rights; Justice
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