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Using Machine Learning to Elucidate the Spatial and Genetic Complexity of the Ascending Aorta

Publication: Miscellaneous

Nekoui, Mahan, James P. Pirruccello, Paolo Di Achille, Seung Hoan Choi, Samuel N. Friedman, Victor Nauffal, Kenney Ng, et al. 2021. “Using Machine Learning to Elucidate the Spatial and Genetic Complexity of the Ascending Aorta.”

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

Publication: Journal Article

Agrawal, Saaket, Marcus D.R. Klarqvist, Connor Emdin, Aniruddh P. Patel, Manish D. Paranjpe, Patrick T. Ellinor, Anthony Philippakis, Kenney Ng, Puneet Batra, and Amit V. Khera. 2021. “Selection of 51 Predictors from 13,782 Candidate Multimodal Features Using Machine Learning Improves Coronary Artery Disease Prediction”. Patterns, 100364.

ECG-Based Deep Learning and Clinical Risk Factors to Predict Atrial Fibrillation

Publication: Journal Article

Khurshid, Shaan, Samuel Friedman, Christopher Reeder, Paolo Di Achille, Nathaniel Diamant, Pulkit Singh, Lia X. Harrington, et al. 2022. “ECG-Based Deep Learning and Clinical Risk Factors to Predict Atrial Fibrillation”. Circulation 145 (2): 122-33.

Abstract 15044: Risk of Myocardial Infarction in Carriers of Familial Hypercholesterolemia Mutations is Modified by Common Variant Genetic Background or Adherence to a Healthy Lifestyle

Publication: Journal Article

Fahed, Akl C, Minxian Wang, Mark Chaffin, Alexander G Bick, Candace Patterson, Pradeep Natarajan, Matthew Lebo, et al. 2019. “Abstract 15044: Risk of Myocardial Infarction in Carriers of Familial Hypercholesterolemia Mutations Is Modified by Common Variant Genetic Background or Adherence to a Healthy Lifestyle”. Circulation 140 (Suppl\_1): A15044—A15044.

Association of machine learning-derived measures of body fat distribution in >40,000 individuals with cardiometabolic diseases

Publication: Journal Article

Agrawal, Saaket, Marcus D. R. Klarqvist, Nathaniel Diamant, Patrick T. Ellinor, Nehal N. Mehta, Anthony Philippakis, Kenney Ng, Puneet Batra, and Amit V. Khera. 2021. “Association of Machine Learning-Derived Measures of Body Fat Distribution in >40,000 Individuals With Cardiometabolic Diseases”. MedRxiv, 2021.05.07.21256854.

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Puneet Batra

Person: Director, Machine Learning, DSP

Puneet Batra is a machine learning scientist, software engineer, and physicist at the Broad Institute of MIT and Harvard. Batra leads the Machine Learning For Health group at the Broad, which leverages machine learning for biological discovery and clinical impact. After an academic career as a...

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

Publication: Miscellaneous

Cunningham, Jonathan W., Paolo Di Achille, Valerie N. Morrill, Lu-Chen Weng, Seung Hoan Choi, Shaan Khurshid, Victor Nauffal, et al. 2021. “Machine Learning to Understand Genetic and Clinical Factors Associated With the Pulse Waveform Dicrotic Notch.”

Physiology as a Lingua Franca for Clinical Machine Learning

Publication: Journal Article

Sarma, Gopal, Erik Reinertsen, and ML4CVD Group. 2020. “Physiology As a Lingua Franca for Clinical Machine Learning”. Patterns 1 (2): 100017.

Clinical and Genetic Associations of Deep Learning-Derived Cardiac Magnetic Resonance-Based Left Ventricular Mass

Publication: Miscellaneous

Khurshid, Shaan, Julieta Lazarte, James P. Pirruccello, Lu-Chen Weng, Seung Hoan Choi, Amelia W. Hall, Xin Wang, et al. 2022. “Clinical and Genetic Associations of Deep Learning-Derived Cardiac Magnetic Resonance-Based Left Ventricular Mass.”