Citation

Zhu YZ, Zhang J, Cheng Q, Deng KF, Ma KJ, Zhang JH, Zhao J, Sun JH, Huang P, Qin ZQ. Fa Yi Xue Za Zhi 2022; 38(1): 14-19.

Copyright

(Copyright © 2022, Si fa bu Si fa jian ding ke xue ji shu yan jiu suo)

DOI

10.12116/j.issn.1004-5619.2021.410404

PMID

35725699

Abstract

Diatom test is the main laboratory test method in the diagnosis of drowning in forensic medicine. It plays an important role in differentiating the antemortem drowning from the postmortem drowning and inferring drowning site. Artificial intelligence (AI) automatic diatom test is a technological innovation in forensic drowning diagnosis which is based on morphological characteristics of diatom, the application of AI algorithm to automatic identification and classification of diatom in tissues and organs. This paper discusses the morphological diatom test methods and reviews the research progress of automatic diatom recognition and classification involving AI algorithms. AI deep learning algorithm can assist diatom testing to obtain objective, accurate, and efficient qualitative and quantitative analysis results, which is expected to become a new direction of diatom testing research in the drowning of forensic medicine in the future.

Language: zh

Keywords

drowning; forensic pathology; review; artificial intelligence; deep learning; diatom test