75 citations · 101 across the 3 of their papers we have counts for
5 papers
Identifying Ventricular Arrhythmias and Their Predictors by Applying Machine Learning Methods to Electronic Health Records in Patients With Hypertrophic Cardiomyopathy(HCM-VAr-Risk Model)
Moumita Bhattacharya, Dai-Yin Lu, Shibani M Kudchadkar +10
Clinical risk stratification for sudden cardiac death (SCD) in hypertrophic cardiomyopathy (HC) employs rules derived from American College of Cardiology Foundation/American Heart…
Machine Learning Methods for Identifying Atrial Fibrillation Cases and Their Predictors in Patients With Hypertrophic Cardiomyopathy: The HCM-AF-Risk Model
Moumita Bhattacharya, Dai-Yin Lu, Ioannis Ventoulis +9
Hypertrophic cardiomyopathy (HCM) patients have a high incidence of atrial fibrillation (AF) and increased stroke risk, even with low risk of congestive heart failure, hypertension…
CathAI: Fully Automated Interpretation of Coronary Angiograms Using Neural Networks
Robert Avram, Jeffrey E. Olgin, Alvin Wan +8
Coronary heart disease (CHD) is the leading cause of adult death in the United States and worldwide, and for which the coronary angiography procedure is the primary gateway for dia…
Using Multitask Learning to Improve 12-Lead Electrocardiogram Classification
J. Weston Hughes, Taylor Sittler, Anthony D. Joseph +3
We develop a multi-task convolutional neural network (CNN) to classify multiple diagnoses from 12-lead electrocardiograms (ECGs) using a dataset comprised of over 40,000 ECGs, with…
DeepHeart: Semi-Supervised Sequence Learning for Cardiovascular Risk Prediction
Brandon Ballinger, Johnson Hsieh, Avesh Singh +8
We train and validate a semi-supervised, multi-task LSTM on 57,675 person-weeks of data from off-the-shelf wearable heart rate sensors, showing high accuracy at detecting multiple…