| Autor: |
Yong-Zheng, Zhu, Ji, Zhang, Qi, Cheng, Kai-Fei, Deng, Kai-Jun, Ma, Jian-Hua, Zhang, Jian, Zhao, Jun-Hong, Sun, Ping, Huang, Zhi-Qiang, Qin |
| Rok vydání: |
2022 |
| Předmět: |
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| Zdroj: |
Fa yi xue za zhi. 38(1) |
| ISSN: |
1004-5619 |
| Popis: |
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.硅藻检验是法医学溺死诊断中的主要实验室检验方法，在鉴别水中尸体生前溺死和死后入水以及推断落水点中发挥了重要作用。人工智能自动化硅藻检验基于硅藻形态学特征，应用人工智能算法对组织器官中的硅藻进行自动化识别和分类，是法医学硅藻检验的一次技术革新。本文从形态学硅藻检验方法展开讨论，并对人工智能算法参与的自动化硅藻识别和分类研究进展进行综述。人工智能深度学习算法可以辅助硅藻检验得到客观、准确、高效的定性定量分析结果，有望成为未来法医学溺死硅藻检验研究的新方向。. |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
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