代表性学术论文: [1] Han C, Que W, Wang S, et al. QRS complexes and T waves localization in multi-lead ECG signals based on deep learning and electrophysiology knowledge[J]. Expert Systems with Applications, 2022, 199: 117187. (SCI-IF:8.665,中科院1区) [2] Han C, Pan S, Que W, et al. Automated localization and severity period prediction of myocardial infarction with clinical interpretability based on deep learning and knowledge graph[J]. Expert Systems with Applications, 2022, 209: 118398. (SCI-IF:8.665,中科院1区) [3] Han C, Sun J, Bian Y, et al. Automated detection and localization of myocardial infarction with interpretability analysis based on deep learning [J]. IEEE Transactions on Instrumentation and Measurement, 2023, 72:1-12.(SCI-IF:5.332,中科院2区) [4] Han C, Shi L. ML-ResNet: a novel network to detect and locate myocardial infarction using 12 leads ECG[J]. Computer Methods and Programs in Biomedicine, 2020, 185: 105138. (SCI-IF:7.027,中科院2区) [5] Han C, Shi L. Automated interpretable detection of myocardial infarction fusing energy entropy and morphological features[J]. Computer Methods and Programs in Biomedicine, 2019, 175: 9-23. (SCI-IF:7.027,中科院2区) 已授权发明专利: [1]基于知识图谱的冠心病多模态数据特征提取方法.ZL202311242845.7,2024-08-06. [2]基于深度学习与诊断规则的心拍形态识别方法及系统. ZL202111651395.8, 2024-03-13. [3]一种基于知识图谱的心肌梗死智能辅助验证方法及系统. ZL202111651413.2, 2024-03-13. [4]一种结合深度学习和电生理知识的多导联心电信号特征点提取方法. ZL202111460169.1, 2023-01.04. [5]一种用于多导联心电信号的特征提取方法及对应监测系统.ZL201910095801.3, 2022-02-11. [6]一种多导联心电信号复合特征提取方法及对应监测系统.ZL201910087975.5, 2021-04-30. |