| 基于人工智能硅藻自动化识别系统的实际案例应用 |
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| 引用本文： | 周圆圆,曹永杰,杨越,王亚丽,邓恺飞,马开军,陈忆九,秦志强,张建华,黄平,张吉,陈丽琴.基于人工智能硅藻自动化识别系统的实际案例应用[J].法医学杂志,2020(2):239-242. |
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| 作者姓名： | 周圆圆 曹永杰 杨越 王亚丽 邓恺飞 马开军 陈忆九 秦志强 张建华 黄平 张吉 陈丽琴 |
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| 作者单位： | 内蒙古医科大学法医学教研室;司法鉴定科学研究院;南京医科大学法医学教研室;上海市刑事科学技术研究院 |
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| 基金项目： | 国家自然科学基金资助项目(81601645,81722027,81801873);“十三五”国家重点研发计划资助项目(2016YFC0800702);上海市法医学重点实验室资助项目(17DZ2273200);上海市司法鉴定专业技术服务平台资助项目(19DZ2290900);上海市法医学重点实验室基金资助项目(KF1802)。 |
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| 摘 要： | 目的探讨人工智能硅藻自动化识别系统在实际案例中的应用,为应用该系统进行硅藻定量分析提供参考,并对该系统所搭载的深度学习模型进行验证。方法收集10例水中尸体的器官进行硅藻硝酸消解,利用数字化切片扫描仪将涂片数字化扫描后,使用人工智能硅藻自动化识别系统进行硅藻的定性定量检测。结果该人工智能硅藻自动化识别系统所搭载的深度学习模型的受试者操作特征(receiver opera?tor characteristic,ROC)曲线的曲线下面积(area under the curve,AUC)达到98.22%,硅藻识别的查准率达到92.45%。结论该人工智能硅藻自动化识别系统实现了硅藻的自动化识别,可用于实际案例中硅藻的辅助检验,并为水中尸体的死因鉴定提供参考依据。
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| 关 键 词： | 法医病理学 人工智能 硅藻类 溺死 |
Application of Artificial Intelligence Automatic Diatom Identification System in Practical Cases |
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| ZHOU Yuan-yuan,CAO Yong-jie,YANG Yue,WANG Ya-li,DENG Kai-fei,MA Kai-jun,CHEN Yijiu,QIN Zhi-qiang,ZHANG Jian-hua,HUANG Ping,ZHANG Ji,CHEN Li-qin.Application of Artificial Intelligence Automatic Diatom Identification System in Practical Cases[J].Journal of Forensic Medicine,2020(2):239-242. |
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| Authors: | ZHOU Yuan-yuan CAO Yong-jie YANG Yue WANG Ya-li DENG Kai-fei MA Kai-jun CHEN Yijiu QIN Zhi-qiang ZHANG Jian-hua HUANG Ping ZHANG Ji CHEN Li-qin |
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| Institution: | (Department of Forensic Medicine,Inner Mongolia Medical University,Hohhot 010030,China;Shang?hai Key Laboratory of Forensic Medicine,Key Laboratory of Forensic Science,Ministry of Justice,Shang?hai Forensic Service Platform,Academy of Forensic Science,Shanghai 200063,China;Department of Fo?rensic Medicine,Nanjing Medical University,Nanjing 210000,China;Shanghai Research Institute of Crimi?nal Science and Technology,Shanghai 200083,China) |
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| 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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| Keywords: | forensic pathology artificial intelligence diatoms death from drowning |
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