Developing a fully applicable machine learning (ML) based sex classification model using linear cranial dimensions

Abstract

Recent advances in artificial intelligence (AI) and machine learning (ML) applications have elevated accomplishments in various scientific fields, primarily those that benefit the economy and society. Contemporary threats, such as armed conflicts, natural and man-made disasters, and illegal immigration, often require fast and innovative but reliable identification aids, in which forensic anthropology has a significant role. However, forensic anthropology has not yet exploited new scientific advances but instead relies on traditionally used methods. The rare studies that employed AI and ML in developing standards for sex and age estimation did not go beyond the conceptual solutions and were not applied to real cases. In this study, on the example of Croatian populations' cranial dimensions, we demonstrated the methodology of developing sex classification models using ML in conjunction with field knowledge, resulting in sex estimation accuracy of more than 95%. To illustrate the necessity of applying scientific results, we developed a web app, CroCrania ( https://crocrania.onrender.com ), that can be used for sex estimation and method validation.

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