心脏传导系统深度学习模型的建立与效能评估  

Establishment and efficacy evaluation of deep learning model for cardiac conduction system

作　　者：张孟周 王敏 钟悦 魏宣 李畅 张海东 赵东 王旭 杨天潼 Zhang Mengzhou;Wang Min;Zhong yue;Wei Xuan;Li Chang;Zhang Haidong;Zhao Dong;Wang Xu;Yang Tiantong(Key Laboratory of Evidence Science(China University of Political Science and Law),Ministry of Education,Beijing 100088,China;Collaborative Innovation Center of Judicial Civilization,Beijing 100088,China)

机构地区：[1]中国政法大学证据科学教育部重点实验室,北京100088 [2]司法文明协同创新中心,北京100088

出　　处：《中国法医学杂志》2023年第6期633-636,共4页Chinese Journal of Forensic Medicine

基　　金：中国政法大学青年教师资助计划项目(10820710);国家重点研发计划青年科学家项目(2022YFC3310300)。

摘　　要：目的 探讨基于深度学习建立的AI模型对心脏传导系统的识别效能。方法 选取17例非猝死案例的心肌和CCS的HE染色切片,以2位具有20年以上CCS诊断经验的主任法医师一致认定是否为CCS病变为金标准。通过Inception V3算法建立AI模型并完成CCS识别的训练和测试,采用混淆矩阵、准确率、精确率、召回率、F1分数、ROC曲线、AUC值等指标评估AI模型效能以及准确率、敏感性和特异性等指标评估人工独立及AI辅助人工两种方式对CCS的识别效能。结果 AI模型识别CCS的准确率为87.3%、精确率为91.9%、召回率为81.9%、F1分数86.6%、AUC值为95.3%,其准确率高于高级职称法医鉴定人员的准确率。AI辅助高级职称法医鉴定人员识别CCS的准确率与人工独立检出相比,差异无统计学意义(p> 0.05),AI辅助中级职称和初级职称法医鉴定人员识别CCS的准确率分别提高了8%和14.33%,差异均有统计学意义(p <0.05),AI辅助初级职称法医鉴定人员识别CCS的准确率高于中级职称法医鉴定人员自主诊断水平。结论 AI模型可用于CCS的自动识别,同时可提升低年资法医鉴定人员对CCS的识别效能,缩小与高年资法医鉴定人员之间的差距。Objective To investigate the recognition efficiency of AI model based on deep learning for cardiac conduction system(CCS).Methods HE staining sections of cardiac muscle and CCS of 17 cases of non-sudden death were selected,and the gold standard was unanimous recognition by 2 forensic pathologists with more than 20 years of CCS diagnosis experience.Inception V3 algorithm was used to establish AI model and complete CCS identification training and testing.Confusion matrix,accuracy,precision,recall,F1 score,ROC curve and AUC value were used to evaluate the effectiveness of AI model,and accuracy,sensitivity and specificity were used to evaluate the efficiency of manual independent and AI-assisted manual recognition for CCS.Results The accuracy of AI model was 87.3%,the precision was 91.9%,the recall was 81.9%,the F1 score was 86.6%,and the AUC value was 95.3%.The accuracy of AI model was higher than that of senior forensic pathologists.There was no statistical significance in the accuracy of AI-assisted senior forensic pathologists in identifying CCS compared with manual independent detection(P>0.05),while the accuracy of AI-assisted intermediate and junior forensic pathologists in identifying CCS was increased by 8%and 14.33%,respectively,with statistical significance(P<0.05).The accuracy rate of AI-assisted junior forensic pathologists to identify CCS was higher than that of intermediate forensic pathologists in self-diagnosis.Conclusion The AI model could be used for the automatic recognition of CCS,and could improve the diagnostic efficiency of CCS and narrow the gap between the forensic pathologists with low experience and that with high experience.

关 键 词：法医学 心脏传导系统 人工智能 Inception V3 效能 

分 类 号：D919.1[医药卫生—法医学]