Jerković Ivan, Bašić Željana, Krešić Elvira, Jerković Nika, Dolić Krešimir, Čavka Mislav, Bedalov Ana, Anđelinović Šimun, Kružić Ivana
University Department of Forensic Sciences, University of Split, Split, Croatia.
Department of Diagnostic and Interventional Radiology, University Hospital Center Zagreb, Zagreb, Croatia.
Sci Rep. 2024 Dec 28;14(1):30969. doi: 10.1038/s41598-024-82073-8.
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.
人工智能（AI）和机器学习（ML）应用的最新进展提升了各个科学领域的成就，主要是那些对经济和社会有益的领域。当代威胁，如武装冲突、自然和人为灾害以及非法移民，通常需要快速、创新但可靠的识别辅助工具，法医人类学在其中发挥着重要作用。然而，法医人类学尚未利用新的科学进展，而是依赖于传统使用的方法。在制定性别和年龄估计标准时采用人工智能和机器学习的罕见研究并未超出概念性解决方案，也未应用于实际案例。在本研究中，以克罗地亚人群的颅骨尺寸为例，我们展示了结合现场知识使用机器学习开发性别分类模型的方法，性别估计准确率超过95%。为了说明应用科学成果的必要性，我们开发了一个网络应用程序CroCrania（https://crocrania.onrender.com），可用于性别估计和方法验证。
