A comprehensive artificial intelligence–enabled electrocardiogram interpretation program

[1]  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.

[2]  Miguel C. Soriano,et al.  A Fast Machine Learning Model for ECG-Based Heartbeat Classification and Arrhythmia Detection , 2019, Front. Phys..

[3]  P. Noseworthy,et al.  Screening for cardiac contractile dysfunction using an artificial intelligence–enabled electrocardiogram , 2019, Nature Medicine.

[4]  A. Ng,et al.  Cardiologist-level arrhythmia detection and classification in ambulatory electrocardiograms using a deep neural network , 2019, Nature Medicine.

[5]  Jichao Zhao,et al.  Robust ECG signal classification for detection of atrial fibrillation using a novel neural network , 2017, 2017 Computing in Cardiology (CinC).

[6]  U. Rajendra Acharya,et al.  Automated detection of arrhythmias using different intervals of tachycardia ECG segments with convolutional neural network , 2017, Inf. Sci..

[7]  H. Wellens,et al.  Computer-Interpreted Electrocardiograms: Benefits and Limitations. , 2017, Journal of the American College of Cardiology.

[8]  Raymond R. Bond,et al.  The role of computerized diagnostic proposals in the interpretation of the 12-lead electrocardiogram by cardiology and non-cardiology fellows , 2017, Int. J. Medical Informatics.

[9]  Sebastian Thrun,et al.  Dermatologist-level classification of skin cancer with deep neural networks , 2017, Nature.

[10]  Subhashini Venugopalan,et al.  Development and Validation of a Deep Learning Algorithm for Detection of Diabetic Retinopathy in Retinal Fundus Photographs. , 2016, JAMA.

[11]  J. Villacastín,et al.  The influence of computerized interpretation of an electrocardiogram reading. , 2016, The American journal of emergency medicine.

[12]  Jonathan R Studnek,et al.  Electrocardiographic diagnosis of ST segment elevation myocardial infarction: An evaluation of three automated interpretation algorithms. , 2016, Journal of electrocardiology.

[13]  Akshay Khandelwal,et al.  The Comparison of Physician to Computer Interpreted Electrocardiograms on ST-elevation Myocardial Infarction Door-to-balloon Times. , 2016, Critical pathways in cardiology.

[14]  Jian Sun,et al.  Deep Residual Learning for Image Recognition , 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[15]  Geoffrey E. Hinton,et al.  Deep Learning , 2015, Nature.

[16]  Jian Sun,et al.  Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification , 2015, 2015 IEEE International Conference on Computer Vision (ICCV).

[17]  Yoshua Bengio,et al.  Understanding the difficulty of training deep feedforward neural networks , 2010, AISTATS.

[18]  A. Shah,et al.  Errors in the computerized electrocardiogram interpretation of cardiac rhythm. , 2007, Journal of electrocardiology.

[19]  Frank Bogun,et al.  Accuracy of electrocardiogram interpretation by cardiologists in the setting of incorrect computer analysis. , 2006, Journal of electrocardiology.

[20]  M. Guglin,et al.  Common errors in computer electrocardiogram interpretation. , 2006, International journal of cardiology.

[21]  Paul Kligfield,et al.  Diagnostic performance of a computer-based ECG rhythm algorithm. , 2005, Journal of electrocardiology.

[22]  W. Weaver,et al.  Misdiagnosis of atrial fibrillation and its clinical consequences. , 2004, The American journal of medicine.

[23]  Philip de Chazal,et al.  Automatic classification of heartbeats using ECG morphology and heartbeat interval features , 2004, IEEE Transactions on Biomedical Engineering.

[24]  L Edenbrandt,et al.  A confident decision support system for interpreting electrocardiograms. , 1999, Clinical physiology.

[25]  E. Antman,et al.  A Neural Network System for Detection of Atrial Fibrillation in Ambulatory Electrocardiograms , 1994, Journal of cardiovascular electrophysiology.

[26]  W J CARBERY,et al.  Computer Extraction of Electrocardiographic Parameters , 1962, Circulation.

[27]  Hubert V. Pipberger,et al.  Digital Recording of Electrocardiographic Data for Analysis by a Digital Computer , 1959 .