Accurate detection of arrhythmias on raw electrocardiogram images: An aggregation attention multi-label model for diagnostic assistance.
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[1] Shuaicong Hu,et al. Classification of multi-lead ECG with deep residual convolutional neural networks , 2022, Physiological measurement.
[2] S. Pratiher,et al. A deep residual inception network with channel attention modules for multi-label cardiac abnormality detection from reduced-lead ECG , 2022, Physiological measurement.
[3] Xiuzhu Yang,et al. 12-Lead ECG arrhythmia classification using cascaded convolutional neural network and expert feature. , 2021, Journal of electrocardiology.
[4] Michael J Ackerman,et al. Detection of Hypertrophic Cardiomyopathy Using a Convolutional Neural Network-Enabled Electrocardiogram. , 2020, Journal of the American College of Cardiology.
[5] Yunpeng Ji,et al. Potential association between COVID-19 mortality and health-care resource availability , 2020, The Lancet Global Health.
[6] T. Lancet. Protecting Chinese doctors , 2020, The Lancet.
[7] Yang Song,et al. Survey on deep learning for pulmonary medical imaging , 2019, Frontiers of Medicine.
[8] Huazhong Yang,et al. A global and updatable ECG beat classification system based on recurrent neural networks and active learning , 2019, Inf. Sci..
[9] Rickey E Carter,et al. An artificial intelligence-enabled ECG algorithm for the identification of patients with atrial fibrillation during sinus rhythm: a retrospective analysis of outcome prediction , 2019, The Lancet.
[10] Z. Zhang,et al. Impact of Dataset Size on Deep Learning-Based Auto Segmentation for Head and Neck Cancer , 2019, International Journal of Radiation Oncology, Biology, Physics.
[11] C. Webster,et al. Examining the Multi-Scalar Unevenness of High-Quality Healthcare Resources Distribution in China , 2019, International journal of environmental research and public health.
[12] Taghi M. Khoshgoftaar,et al. A survey on Image Data Augmentation for Deep Learning , 2019, Journal of Big Data.
[13] Michael J Ackerman,et al. Development and Validation of a Deep-Learning Model to Screen for Hyperkalemia From the Electrocardiogram. , 2019, JAMA cardiology.
[14] Kipp W. Johnson,et al. Deep learning for cardiovascular medicine: a practical primer. , 2019, European heart journal.
[15] Xin Sun,et al. Evaluation and accurate diagnoses of pediatric diseases using artificial intelligence , 2019, Nature Medicine.
[16] P. Noseworthy,et al. Screening for cardiac contractile dysfunction using an artificial intelligence–enabled electrocardiogram , 2019, Nature Medicine.
[17] Sasank Chilamkurthy,et al. Deep learning algorithms for detection of critical findings in head CT scans: a retrospective study , 2018, The Lancet.
[18] David Tsay,et al. From Machine Learning to Artificial Intelligence Applications in Cardiac Care. , 2018, Circulation.
[19] Jayme G. A. Barbedo,et al. Impact of dataset size and variety on the effectiveness of deep learning and transfer learning for plant disease classification , 2018, Comput. Electron. Agric..
[20] Mohammad Bagher Shamsollahi,et al. Sleep Apnea Detection from Single-Lead ECG Using Features Based on ECG-Derived Respiration (EDR) Signals , 2018, IRBM.
[21] Jeroen J. Bax,et al. Machine Learning for Electrocardiographic Diagnosis of Left Ventricular Early Diastolic Dysfunction. , 2018, Journal of the American College of Cardiology.
[22] Andrew Y. Ng,et al. Cardiologist-Level Arrhythmia Detection with Convolutional Neural Networks , 2017, ArXiv.
[23] Bram van Ginneken,et al. A survey on deep learning in medical image analysis , 2017, Medical Image Anal..
[24] Lubomir M. Hadjiiski,et al. Deep Learning in Medical Image Analysis. , 2020, Advances in experimental medicine and biology.
[25] Sebastian Thrun,et al. Dermatologist-level classification of skin cancer with deep neural networks , 2017, Nature.
[26] Yuan Yu,et al. TensorFlow: A system for large-scale machine learning , 2016, OSDI.
[27] Erik Schultes,et al. The FAIR Guiding Principles for scientific data management and stewardship , 2016, Scientific Data.
[28] Moncef Gabbouj,et al. Real-Time Patient-Specific ECG Classification by 1-D Convolutional Neural Networks , 2016, IEEE Transactions on Biomedical Engineering.
[29] Jian Sun,et al. Deep Residual Learning for Image Recognition , 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[30] Sergey Ioffe,et al. Rethinking the Inception Architecture for Computer Vision , 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[31] Geoffrey E. Hinton,et al. Deep Learning , 2015, Nature.
[32] R. Ortega,et al. Videos in clinical medicine. Electrocardiographic monitoring in adults. , 2015, The New England journal of medicine.
[33] E. W. Hancock,et al. AHA/ACCF/HRS recommendations for the standardization and interpretation of the electrocardiogram: part IV: the ST segment, T and U waves, and the QT interval: a scientific statement from the American Heart Association Electrocardiography and Arrhythmias Committee, Council on Clinical Cardiology; the , 2009, Journal of the American College of Cardiology.
[34] G.B. Moody,et al. The impact of the MIT-BIH Arrhythmia Database , 2001, IEEE Engineering in Medicine and Biology Magazine.
[35] Jeffrey M. Hausdorff,et al. Physionet: Components of a New Research Resource for Complex Physiologic Signals". Circu-lation Vol , 2000 .
[36] G. Lip,et al. Mobile Health Technology for Atrial Fibrillation Screening Using Photoplethysmography-Based Smart Devices: The HUAWEI Heart study. , 2019, Journal of the American College of Cardiology.
[37] E. W. Hancock,et al. AHA/ACCF/HRS recommendations for the standardization and interpretation of the electrocardiogram: part VI: acute ischemia/infarction: a scientific statement from the American Heart Association Electrocardiography and Arrhythmias Committee, Council on Clinical Cardiology; the American College of Card , 2009, Journal of the American College of Cardiology.
[38] A. Hoes,et al. [Guidelines on cardiovascular disease prevention in clinical practice]. , 2005, Revue medicale de Liege.
[39] H. W. Day. Preliminary studies of an acute coronary care area. , 1963, The Journal-lancet.