ML4H Publications

2023

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

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

2022

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.

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

Deep Learning to Predict Cardiac Magnetic Resonance–Derived Left Ventricular Mass and Hypertrophy From 12-Lead ECGs

Circulation: Cardiovascular Imaging
Shaan Khurshid, Samuel Friedman, James P. Pirruccello, Paolo Di Achille, Nathaniel Diamant, Christopher D. Anderson, Patrick T. Ellinor, Puneet Batra, Jennifer E. Ho, Anthony A. Philippakis, and Steven A. Lubitz.

Deep learning to estimate cardiac magnetic resonance–derived left ventricular mass,
Cardiovascular Digital Health Journal

Shaan Khurshid, Samuel Freesun Friedman, James P. Pirruccello, Paolo Di Achille, Nathaniel Diamant, Christopher D. Anderson, Patrick T. Ellinor, Puneet Batra, Jennifer E. Ho, Anthony A. Philippakis, and Steven A. Lubitz.

Cohort Design and Natural Language Processing to Reduce Bias in Electronic Health Records Research: The Community Care Cohort Project
npj - digital medicine
S. Khurshid, C. Reeder, L. X. Harrington, P. Singh, G. Sarma, S. F. Friedman, P. Di Achille, N. Diamant, J. W. Cunningham, A. C. Turner, E. S. Lau, J. S. Haimovich, M. A. Al-Alusi, X. Wang, M. D. R. Klarqvist, J. M. Ashburner, C. Diedrich, M. Ghadessi, J. Mielke, H. M. Eilken, A. McElhinney, A. Derix, S. J. Atlas, P. T. Ellinor, A. A. Philippakis, C. D. Anderson, J. E. Ho, P. Batra, and S. A. Lubitz.

Machine learning enables new insights into genetic contributions to liver fat accumulation
Cell Genomics
M. E. Haas, J. P. Pirruccello, S. N. Friedman, M. Wang, C. A. Emdin, V. H. Ajmera, T. G. Simon, J. R. Homburger, X. Guo, M. Budoff, K. E. Corey, A. Y. Zhou, A. Philippakis, P. T. Ellinor, R. Loomba, P. Batra, and A. V. Khera.

Selection of 51 predictors from 13,782 candidate multimodal features using machine learning improves coronary artery disease prediction

Patterns

S. Agrawal, M. D.R. Klarqvist, C. Emdin, A. P. Patel, M. D. Paranjpe, P. T. Ellinor, A. Philippakis, K. Ng, P. Batra, and A. V. Khera.

Machine Learning to Understand Genetic and Clinical Factors Associated with the Pulse Waveform Dicrotic Notch,
Circulation

J. W. Cunningham, P. D. Achille, V. N. Morrill, L.-C. Weng, S. H. Choi, S. Khurshid, V. Nauffal, J. P Pirruccello, S. D. Solomon, P. Batra, J. E. Ho, A. A. Philippakis, P. T. Ellinor, and S. A. Lubitz.

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