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Zhou YY, Cao YJ, Yang Y, Wang YL, Deng KF, Ma KJ, Chen YJ, Qin ZQ, Zhang JH, Huang P, Zhang J, Chen LQ. Application of Artificial Intelligence Automatic Diatom Identification System in Practical Cases. Fa Yi Xue Za Zhi 2020; 36:239-242. [PMID: 32530174 DOI: 10.12116/j.issn.1004-5619.2020.02.017] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Received: 11/18/2019] [Indexed: 11/30/2022]
Abstract
Abstract Objective To discuss the application of artificial intelligence automatic diatom identification system in practical cases, to provide reference for quantitative diatom analysis using the system and to validate the deep learning model incorporated into the system. Methods Organs from 10 corpses in water were collected and digested with diatom nitric acid; then the smears were digitally scanned using a digital slide scanner and the diatoms were tested qualitatively and quantitatively by artificial intelligence automatic diatom identification system. Results The area under the curve （AUC） of the receiver operator characteristic （ROC） curve of the deep learning model incorporated into the artificial intelligence automatic diatom identification system, reached 98.22% and the precision of diatom identification reached 92.45%. Conclusion The artificial intelligence automatic diatom identification system is able to automatically identify diatoms, and can be used as an auxiliary tool in diatom testing in practical cases, to provide reference to drowning diagnosis.
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Affiliation(s)
- Y Y Zhou
- Department of Forensic Medicine, Inner Mongolia Medical University, Hohhot 010030, China.,Shanghai Key Laboratory of Forensic Medicine, Key Laboratory of Forensic Science, Ministry of Justice, Shanghai Forensic Service Platform, Academy of Forensic Science, Shanghai 200063, China
| | - Y J Cao
- Department of Forensic Medicine, Nanjing Medical University, Nanjing 210000, China
| | - Y Yang
- Department of Forensic Medicine, Inner Mongolia Medical University, Hohhot 010030, China
| | - Y L Wang
- Department of Forensic Medicine, Inner Mongolia Medical University, Hohhot 010030, China
| | - K F Deng
- Shanghai Key Laboratory of Forensic Medicine, Key Laboratory of Forensic Science, Ministry of Justice, Shanghai Forensic Service Platform, Academy of Forensic Science, Shanghai 200063, China
| | - K J Ma
- Shanghai Research Institute of Criminal Science and Technology, Shanghai 200083, China
| | - Y J Chen
- Shanghai Key Laboratory of Forensic Medicine, Key Laboratory of Forensic Science, Ministry of Justice, Shanghai Forensic Service Platform, Academy of Forensic Science, Shanghai 200063, China
| | - Z Q Qin
- Shanghai Key Laboratory of Forensic Medicine, Key Laboratory of Forensic Science, Ministry of Justice, Shanghai Forensic Service Platform, Academy of Forensic Science, Shanghai 200063, China
| | - J H Zhang
- Shanghai Key Laboratory of Forensic Medicine, Key Laboratory of Forensic Science, Ministry of Justice, Shanghai Forensic Service Platform, Academy of Forensic Science, Shanghai 200063, China
| | - P Huang
- Shanghai Key Laboratory of Forensic Medicine, Key Laboratory of Forensic Science, Ministry of Justice, Shanghai Forensic Service Platform, Academy of Forensic Science, Shanghai 200063, China
| | - J Zhang
- Shanghai Key Laboratory of Forensic Medicine, Key Laboratory of Forensic Science, Ministry of Justice, Shanghai Forensic Service Platform, Academy of Forensic Science, Shanghai 200063, China
| | - L Q Chen
- Department of Forensic Medicine, Inner Mongolia Medical University, Hohhot 010030, China
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