ML4H Publications

2023

Deep Learning-Enabled Assessment of Left Heart Structure and Function Predicts Cardiovascular Outcomes, 
Journal of the American College of Cardiology
E. S. Lau, P. Di Achille, K. Kopparapu, C. T. Andrews, P. Singh, C. Reeder, M. Al-Alusi, S. Khurshid, J. S. Haimovich, P. T. Ellinor, M. H. Picard, P. Batra, S. A. Lubitz, and J. E. Ho

Deep learned representations of the resting 12-lead electrocardiogram to predict V̇O2 at peak exercise, 
European Journal of Preventive Cardiology
S. Khurshid, T. W Churchill, N. Diamant, P. Di Achille, C. Reeder, P. Singh, S. F Friedman, M. M Wasfy, G. A Alba, B. A Maron, D. M Systrom, B. M Wertheim, P. T Ellinor, J. E Ho, A. L Baggish, P. Batra, S. A Lubitz, J S. Guseh

Natural Language Processing for Adjudication of Heart Failure Hospitalizations in a Multi-Center Clinical Trial, 
JAMA Cardiology
Cunningham, J. W., Singh, P., Reeder, C., Claggett, B., Marti-Castellote, P. M., Lau, E. S., Khurshid, S., Batra, P., Lubitz, S. A., Maddah, M., Philippakis, A., Desai, A. S., Ellinor, P. T., Vardeny, O., Solomon, S. D., & Ho, J. E. 

The Genetic Determinants of Aortic Distention, 
Journal of the American College of Cardiology
J. P. Pirruccello, J. T. Rämö, S. H. Choi, M. D. Chaffin, S. Kany, M. Nekoui, E. L. Chou, S. J. Jurgens, S. F. Friedman, D. Juric, J. R. Stone, P. Batra, K. Ng, A. A. Philippakis, M. E. Lindsay, and P. T. Ellinor

Genetic Susceptibility to Atrial Fibrillation Identified via Deep Learning of 12-lead Electrocardiograms, 
Circulation: Genomic and Precision Medicine
X. Wang, S. Khurshid, S. H. Choi, S. Friedman, L.-C. Weng, C. Reeder, J. P. Pirruccello, P. Singh, E. S. Lau, R. Venn, N. Diamant, P. Di Achille, A. Philippakis, C. D. Anderson, J. E. Ho, P. T. Ellinor, P. Batra, S. A. Lubitz

Genetics of Myocardial Interstitial Fibrosis in the Human Heart and Association with Disease, 
Nature Genetics
V. Nauffal, P. Di Achille, M. D. R. Klarqvist, J. W. Cunningham, M. C. Hill, J. P. Pirruccello, L-C. Weng, V. N. Morrill, S. H. Choi, S. Khurshid, S. F. Friedman, M. Nekoui, C. Roselli, K. Ng, A. A. Philippakis, P. Batra, P. T. Ellinor & S. A. Lubitz

DropFuse: A Cross-Modal Autoencoder Framework Learns Holistic Representations of Cardiovascular State, 
Nature Communications
A. Radhakrishnan, S. F. Friedman, S. Khurshid, K. Ng, P. Batra, S. Lubitz, A. Philippakis, C. Uhler

Clinical and Genetic Associations of Deep Learning-Derived Cardiac Magnetic Resonance-Based Left Ventricular Mass, 
Nature Communications
S. Khurshid, J. Lazarte, J.P. Pirruccello, L.-C. Weng, S. H. Choi, A. W. Hall, X. Wang, S. F. Friedman, V. Nauffal, K. J. Biddinger, K. G. Aragam, P. Batra, J. E. Ho, A. A. Philippakis, P. T. Ellinor & S. A. Lubitz

Artificial Intelligence Enabled Classification of Hypertrophic Heart Diseases Using Electrocardiograms, 
Cardiovascular Digital Health Journal
J. S. Haimovich, N. Diamant, S. Khurshid, P. D. Achille, C. Reeder, S. Friedman, P. Singh, W. Spurlock, P. T. Ellinor, A. Philippakis, P. Batra, J. E. Ho, S. A. Lubitz

Natural Language Processing for Adjudication of Heart Failure in the Electronic Health Record, 
JACC: Heart Failure
J. W. Cunningham, P. Singh, C. Reeder, E. S. Lau, S. Khurshid, X. Wang, P. T. Ellinor, S. A. Lubitz, P. Batra, and J. E. Ho

2022

One clinician is all you need: Data-Efficient NLP Measurement Extraction from Cardiac MRI Reports, 
JMIR Medical Informatics
P Singh, J Haimovich, C Reeder, S Khurshid, ES Lau, JW Cunningham, A Philippakis, CD Anderson, JE Ho, SA Lubitz, P Batra

Deep learning on resting electrocardiogram to identify impaired heart rate recovery, 
Cardiovascular Digital Health Journal
N. Diamant, P. Di Achille, L-C Weng, E. S Lau, S. Khurshid, S. Friedman, C. r Reeder, P. Singh, X. Wang, G. Sarma, M. Ghadessi, J. Mielke, E. Elci, I. Kryukov, H. M Eilken, A. Derix, P.T Ellinor, C. D Anderson, A. A Philippakis, P. Batra, S. A Lubitz, J. E Ho

Genetic analysis of right heart structure and function in 40,000 people, 
Nature Genetics
J. P. Pirruccello, P. D. Achille, V. Nauffal, M. Nekoui, S. F. Friedman, M. D. R. Klarqvist, M. D. Chaffin, L.-C. Weng, J. W. Cunningham, S. Khurshid, C. Roselli, H. Lin, S. Koyama, K. Ito, Y. Kamatani, I. Komuro, The BioBank Japan Project, S. J. Jurgens, E. J. Benjamin, P. Batra, P. Natarajan, K. Ng, U. Hoffmann, S. A. Lubitz, J. E. Ho, M. E. Lindsay, A. A. Philippakis, P. T. Ellinor

Spatially Distinct Genetic Determinants of Aortic Dimensions Influence Risks of Aneurysm and Stenosis 
Journal of the American College of Cardiology
M. Nekoui, J. P. Pirruccello, P. Di Achille, S. H. Choi, S. N. Friedman, V. Nauffal, K. Ng, P. Batra, J. E. Ho, A. A. Philippakis, S. A. Lubitz, M. E. Lindsay, P. T. Ellinor

A Deep Learning Model for Inferring Elevated Pulmonary Capillary Wedge Pressures From the 12-Lead Electrocardiogram, 
JACC: Advances
D. E. Schlesinger, N. Diamant, A. Raghu, E. Reinertsen, K. Young, P. Batra, E. Pomerantsev, and C. M. Stultz

Development of a Prediction Model for Ascending Aortic Diameter Among Asymptomatic Individuals 
JAMA 
J. P. Pirruccello, H. Lin, S. Khurshid, M. Nekoui, L.-C. Weng, R. S. Vasan, E. M. Isselbacher, E. J. Benjamin, S. A. Lubitz, M. E. Lindsay, P. T. Ellinor

Estimating body fat distribution - a driver of cardiometabolic health - from silhouette images
npj - digital medicine
M. D.R. Klarqvist, S. Agrawal, N. Diamant, P. T. Ellinor, A. Philippakis, K. Ng, P. Batra, and A. V. Khera

ECG-Based Deep Learning and Clinical Risk Factors to Predict Atrial Fibrillation
Circulation
S. Khurshid, S. Friedman, C. Reeder, P. Di Achille, N. Diamant, P. Singh, Lia X. Harrington, X. Wang, M. A. Al-Alusi, G. Sarma, A. S. Foulkes, P. T. Ellinor, C. D. Anderson, J. E. Ho, A. A. Philippakis, P. Batra, and S. A. Lubitz.

Deep learning enables genetic analysis of the human thoracic aorta, 
Nature Genetics
J. P. Pirruccello, M. D. Chaffin, E. L. Chou, S. J. Fleming, Honghuang Lin, M. Nekoui, S. Khurshid, S. F. Friedman, A. G. Bick, Alessandro Arduini, L-C Weng, S. H. Choi, A-D Akkad, P. Batra, N. R. Tucker, A. W. Hall, C. Roselli, E. J. Benjamin, S. K. Vellarikkal, Rajat M. Gupta, C. M. Stegmann, D. Juric, J. R. Stone, R. S. Vasan, J. E. Ho, U. Hoffmann, S.  A. Lubitz, A.  A. Philippakis, M. E. Lindsay, and P. T. Ellinor. 

Patient contrastive learning: A performant, expressive, and practical approach to electrocardiogram modeling,
PLOS Computational Biology 
N. Diamant, E. Reinertsen, S. Song, A. D. Aguirre, C. M. Stultz, and P. Batra. 

2021

2020

Analysis of cardiac magnetic resonance imaging in 36,000 individuals yields genetic insights into dilated cardiomyopathy
Nature Communications
J. P. Pirruccello, A. Bick, M. Wang, M. Chaffin, S. Friedman, J. Yao, X. Guo, B. A. Venkatesh, K. D. Taylor, W. S. Post, S. Rich, J. A. C. Lima, J. I. Rotter, A. Philippakis, S. A. Lubitz, P. T. Ellinor, A. V. Khera, S. Kathiresan, and K. G. Aragam