Galante Nicola, Cotroneo Rosy, Furci Domenico, Lodetti Giorgia, Casali Michelangelo Bruno
Healthcare Accountability Lab, Institute of Legal Medicine of Milan, University of Milan, Via Luigi Mangiagalli 37, 20133, Milan, Italy.
Department of Biomedical Sciences for Health, Institute of Legal Medicine of Milan, University of Milan, Via Luigi Mangiagalli 37, 20133, Milan, Italy.
Int J Legal Med. 2023 Mar;137(2):445-458. doi: 10.1007/s00414-022-02928-5. Epub 2022 Dec 12.
In recent years, new studies based on artificial intelligence (AI) have been conducted in the forensic field, posing new challenges and demonstrating the advantages and disadvantages of using AI methodologies to solve forensic well-known problems. Specifically, AI technology has tried to overcome the human subjective bias limitations of the traditional approach of the forensic sciences, which include sex prediction and age estimation from morphometric measurements in forensic anthropology or evaluating the third molar stage of development in forensic odontology. Likewise, AI has been studied as an assisting tool in forensic pathology for a quick and easy identification of the taxonomy of diatoms. The present systematic review follows the PRISMA 2020 statements and aims to explore an emerging topic that has been poorly analyzed in the forensic literature. Benefits, limitations, and forensic implications concerning AI are therefore highlighted, by providing an extensive critical review of its current applications on forensic sciences as well as its future directions. Results are divided into 5 subsections which included forensic anthropology, forensic odontology, forensic pathology, forensic genetics, and other forensic branches. The discussion offers a useful instrument to investigate the potential benefits of AI in the forensic fields as well as to point out the existing open questions and issues concerning its application on real-life scenarios. Procedural notes and technical aspects are also provided to the readers.
近年来,法医学领域开展了基于人工智能(AI)的新研究,带来了新的挑战,同时也展现了使用人工智能方法解决法医学常见问题的利弊。具体而言,人工智能技术试图克服法医学传统方法中人类主观偏见的局限性,这些局限性包括法医人类学中通过形态测量进行性别预测和年龄估计,或法医牙科学中评估第三磨牙发育阶段。同样,人工智能已被研究作为法医病理学中的辅助工具,用于快速轻松地识别硅藻的分类。本系统评价遵循PRISMA 2020声明,旨在探索一个在法医学文献中分析较少的新兴话题。因此,通过对人工智能在法医学当前应用及其未来方向进行广泛的批判性综述,突出了其益处、局限性和法医学意义。结果分为五个小节,包括法医人类学、法医牙科学、法医病理学、法医遗传学和其他法医分支。讨论提供了一个有用的工具,以研究人工智能在法医学领域的潜在益处,并指出其在现实场景应用中存在的未解决问题。还向读者提供了程序说明和技术方面的内容。
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