Zou Y, Zhuang C, Fang Q, Li F
Department of Pathology, Second Affiliated Hospital of Zhejiang University, School of Medicine, Hangzhou 310000, China.
Criminal Investigation Department, Fuzhou Police Office, Fuzhou 350000, China.
Fa Yi Xue Za Zhi. 2020 Feb;36(1):86-90. doi: 10.12116/j.issn.1004-5619.2020.01.017.
The estimation of postmortem interval （PMI） is a core issue in forensic practice. A large amount of time-dependent data can be produced in the decomposition process of a body, however, such multidimensional data cannot be comprehensively and effectively analyzed and utilized by any existing conventional PMI estimation method. As a rapidly developing information technology, artificial intelligence （AI） has significant advantages in big data processing, due to it's comprehensiveness, efficiency and automation. Some scholars have already applied it to researches on the estimation of PMI, showing it's significant advantages in terms of accuracy and development prospect. This article reviews the significance, mode and progress of application of AI in PMI estimation and provides some suggestions and prospects for future study.
死后间隔时间（PMI）的估计是法医学实践中的核心问题。在尸体分解过程中会产生大量随时间变化的数据，然而，任何现有的传统PMI估计方法都无法对这些多维数据进行全面有效的分析和利用。作为一种快速发展的信息技术，人工智能（AI）在大数据处理方面具有显著优势，因其具有全面性、高效性和自动化。一些学者已经将其应用于PMI估计的研究中，显示出其在准确性和发展前景方面的显著优势。本文综述了人工智能在PMI估计中的应用意义、模式和进展，并为未来的研究提供了一些建议和展望。
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