Kataria Suraj, Shinkre Rohan, Jain Sonal, Saraswathy Kallur Nava, Sachdeva Mohinder Pal, Kumar Kp Mohan
Department of Forensic Sciences, School of Basic and Applied Sciences, K.R. Mangalam University, Gurugram, Haryana, India.
Central Research Wing, KLE Society's Institute of Dental Sciences, Bengaluru, Karnataka, India.
J Oral Maxillofac Pathol. 2024 Jul-Sep;28(3):515-525. doi: 10.4103/jomfp.jomfp_546_23. Epub 2024 Oct 15.
This study aimed to investigate the prevalence of dental traits and anomalies in five North Indian populations (Khas Bodhi, Jaat, Khatri, Garhwali, and Gujjar) and predict the population of origin based on these traits and anomalies for forensic applications.
We assessed dental traits and anomalies in 454 individuals through intraoral examination. Neural network analysis was employed to predict the population of origin based on a combination of dental traits and anomalies.
Shovel-shaped incisors exhibited the highest prevalence among the studied traits and anomalies, occurring in 65.4% of the sample. Moreover, shovel-shaped incisors were found to be the most important predictor of population. Neural network analysis indicated that the most accurate population prediction among the studied populations was for the Garhwali origin, achieving a recall rate of 78.3%. While this may appear relatively low, it is crucial to emphasise that the proposed method serves as a corroborative tool for various forensic investigations.
This study suggests that dental traits and anomalies can be valuable in predicting the population of origin within Indian populations for forensic purposes. The work enhances the forensic identification process by providing an additional layer of evidence for consideration in identifying both individuals and their ethnic backgrounds. Further research is necessary to enhance the robustness of prediction models.
本研究旨在调查印度北部五个群体（卡斯菩提、贾特、卡特里、加瓦尔利和古吉拉特）的牙齿特征和异常情况，并基于这些特征和异常情况预测法医学应用中的人口来源。
我们通过口腔检查评估了454名个体的牙齿特征和异常情况。采用神经网络分析，根据牙齿特征和异常情况的组合来预测人口来源。
在所研究的特征和异常情况中，铲形门齿的发生率最高，样本中65.4%的个体有此特征。此外，铲形门齿被发现是人口的最重要预测指标。神经网络分析表明，在所研究的群体中，对加瓦尔利群体来源的预测最为准确，召回率达到78.3%。虽然这一比例可能相对较低，但必须强调的是，所提出的方法可作为各种法医学调查的佐证工具。
本研究表明，牙齿特征和异常情况对于法医学目的预测印度人群体的人口来源可能具有重要价值。这项工作通过提供额外的证据层，为识别个体及其种族背景提供了更多考虑因素，从而加强了法医学鉴定过程。需要进一步研究以提高预测模型的稳健性。
