[1] |
戚厚兴,高静. 恶性心律失常事件及心性猝死预测的研究进展[J]. 心血管病学进展, 1995,16(5):263-265.
|
[2] |
吴屹,白敏聪. 常规心电图与动态心电图用于冠心病心律失常诊断的临床对比研究[J]. 中国基层医药, 2015(13):2056-2057.
|
[3] |
于华,梁伟,张官鹏. 冠心病患者采用动态心电图诊断的临床意义[J]. 中国实验诊断学, 2015,19(8):1292-1294.
|
[4] |
DOTSINSKY I. Clifford Gari D, Azuaje Francisco, McSharry Patrick E, Eds: Advanced methods and tools for ECG analysis[J].Biomedical Engineering Online, 2007,6(1) : Article Number 18. DOI: 10.1186/1475-925X-6-18.
|
[5] |
刘守华,王小松,刘昱. 基于深度学习的临床心电图分类算法[J]. 计算机与现代化, 2021(8):52-57.
|
[6] |
YE C, COIMBRA M T, KUMAR B V K V. Arrhythmia detection and classification using morphological and dynamic features of ECG signals[C]// 2010 Annual International Conference of the IEEE Engineering in Medicine and Biology. 2010:1918-1921.
|
[7] |
KUTLU Y, KUNTALP D. A multi-stage automatic arrhythmia recognition and classification system[J]. Computers in Biology and Medicine, 2011,41(1):37-45.
|
[8] |
王刚,饶妮妮,张瑛. 基于高阶统计量的盲源提取算法获取房颤信号[J]. 中国科学:E辑, 2008,38(12):2212-2225.
|
[9] |
冯俊,邱雅竹,莫智文. 基于小波特征提取的多导联心电图神经网络分类[J]. 第三军医大学学报, 2006, 28(8):857-858.
|
[10] |
CHEN J T, YU H Y, FENG R W, et al. Flow-mixup: Classifying multi-labeled medical images with corrupted labels[C]// 2020 IEEE International Conference on Bioinformatics and Biomedicine (BIBM). 2020:534-541.
|
[11] |
方跃奇,封根泉,郭静男. 心电信号的功率谱特征及其生理意义[J]. 北京生物医学工程, 1986,1(1):69-75.
|
[12] |
MARTIS R J, ACHARYA U R, PRASAD H, et al. Application of higher order statistics for atrial arrhythmia classification[J]. Biomedical Signal Processing and Control, 2013,8(6):888-900.
|
[13] |
ACHARYA U R, FUJITA H, ADAM M, et al. Automated characterization of arrhythmias using nonlinear features from tachycardia ECG beats[C]// 2016 IEEE International Conference on Systems, Man, and Cybernetics (SMC). 2016:533-538
|
[14] |
YE C, KUMAR B V K V, COIMBRA M T. Heartbeat classification using morphological and dynamic features of ECG signals [J]. IEEE Transactions on Biomedical Engineering, 2012,59(10):2930-2941.
|
[15] |
刘丹枫,刘建霞. 面向深度学习过拟合问题的神经网络模型[J]. 湘潭大学自然科学学报, 2018,40(2): 96-99.
|
[16] |
YILDIRIM [O]. A novel wavelet sequence based on deep bidirectional LSTM network model for ECG signal classification[J]. Computers in Biology and Medicine, 2018,96:189-202.
|
[17] |
CHU J H, WANG H, LU W. A noval two-lead arrhythmia classification system based on CNN and LSTM[J]. Journal of Mechanics in Medicine and Biology, 2019,19(3):1950004.
|
[18] |
SELLAMI A, HWANG H. A robust deep convolutional neural network with batch-weighted loss for heartbeat classification[J]. Expert Systems with Applications, 2019,122(C):75-84.
|
[19] |
汤明,姚剑,陈泽宽,等. 基于物联网的可穿戴式动态心电实时监测终端设计与实现[J]. 中国医疗器械杂志, 2018,42(3):161-165.
|
[20] |
姜海燕,刘昊天,舒欣,等. 基于最大均值差异的多标记迁移学习算法[J]. 信息与控制, 2016,45(4):463-470.
|
[21] |
SHI H T, WANG H R, ZHANG F, et al. Inter-patient heartbeat classification based on region feature extraction and ensemble classifier[J]. Biomedical Signal Processing and Control, 2019,51(3):97-105.
|
[22] |
XU S S, MAK M W, CHEUNG C C. Towards end-to-end ECG classification with raw signal extraction and deep neural networks[J]. IEEE Journal of Biomedical and Health Informatics, 2019,23(4):1574-1584.
|
[23] |
王超学,张涛,马春森. 面向不平衡数据集的改进型SMOTE算法[J]. 计算机科学与探索, 2014,8(6):727-734.
|
[24] |
LIN T, GOYAL P, GIRSHICK R, et al. Focal loss for dense object detection[C]// 2017 IEEE International Conference on Computer Vision (ICCV). 2017:2999-3007.
|
[25] |
YU S N, CHOU K T. Integration of independent component analysis and neural networks for ECG beat classification[J]. Expert Systems with Applications, 2008,34(4):2841-2846.
|
[26] |
ACHARYA U R, OH S L, HAGIWARA Y, et al. A deep convolutional neural network model to classify heartbeats[J]. Computers in Biology and Medicine, 2017,89:389-396.
|
[27] |
王文刀,王润泽,魏鑫磊,等. 基于堆叠式双向LSTM的心电图自动识别算法[J]. 计算机科学, 2020,47(7):118-124.
|
[28] |
李传栋,邱磊,于雁. 基于改进残差密集网络的心律失常自动分类[J]. 计算机与现代化, 2021(11):106-111.
|