@article{ref1,
title="Research progress of automatic diatom test by artificial intelligence",
journal="Fa Yi Xue Za Zhi",
year="2022",
author="Zhu, Yong-Zheng and Zhang, Ji and Cheng, Qi and Deng, Kai-Fei and Ma, Kai-Jun and Zhang, Jian-Hua and Zhao, Jian and Sun, Jun-Hong and Huang, Ping and Qin, Zhi-Qiang",
volume="38",
number="1",
pages="14-19",
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.<p /> <p>Language: zh</p>",
language="zh",
issn="1004-5619",
doi="10.12116/j.issn.1004-5619.2021.410404",
url="http://dx.doi.org/10.12116/j.issn.1004-5619.2021.410404"
}