Khurshid, Shaan

Deep learning enables genetic analysis of the human thoracic aorta

Pirruccello, J. P., Chaffin, M. D., Chou, E. L., Fleming, S. J., Lin, H., Nekoui, M., Khurshid, S., Friedman, S. F., Bick, A. G., Arduini, A., et al. (2022) · Nature Genetics

Genetic Associations and EpidemiologyAortic Disease and Treatment Approaches

Cited by 210

Accelerometer-derived "weekend warrior" physical activity and incident cardiovascular disease

Khurshid, S., Al-Alusi, M. A., Churchill, T. W., Guseh, J. S., & Ellinor, P. T. (2023) · JAMA

Physical Activity and HealthCardiovascular and exercise physiology

Cited by 204

Cross-modal autoencoder framework learns holistic representations of cardiovascular state

Radhakrishnan, A., Friedman, S. F., Khurshid, S., Ng, K., Batra, P., Lubitz, S. A., Philippakis, A. A., & Uhler, C. (2023) · Nature Communications

ECG Monitoring and AnalysisMachine Learning in Healthcare

Cited by 82

Wearable accelerometer-derived physical activity and incident disease

Khurshid, S., Weng, L.-C., Nauffal, V., Pirruccello, J. P., Venn, R. A., Al-Alusi, M. A., Benjamin, E. J., Ellinor, P. T., & Lubitz, S. A. (2022) · npj Digital Medicine

Physical Activity and HealthContext-Aware Activity Recognition Systems

Cited by 63

Natural Language Processing for Adjudication of Heart Failure in a Multicenter Clinical Trial: A Secondary Analysis of a Randomized Clinical Trial

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., et al. (2024) · JAMA Cardiology

Artificial Intelligence in HealthcareHeart Failure Treatment and Management

Cited by 38

Rare Genetic Variants in LDLR , APOB , and PCSK9 Are Associated With Aortic Stenosis

Rämö, J. T., Jurgens, S. J., Kany, S., Choi, S. H., Wang, X., Smirnov, A. N., Friedman, S. F., Maddah, M., Khurshid, S., Ellinor, P. T., et al. (2024) · Circulation

Lipoproteins and Cardiovascular HealthCardiac Valve Diseases and Treatments

Cited by 26

Natural language processing for adjudication of heart failure in the electronic health record

Cunningham, J. W., Singh, P., Reeder, C., Lau, E. S., Khurshid, S., Wang, X., Ellinor, P. T., Lubitz, S. A., Batra, P., & Ho, J. E. (2023) · JACC: Heart Failure

Machine Learning in HealthcareHeart Failure Treatment and Management

Cited by 21

Foundation models for electrocardiogram interpretation: clinical implications

Nolin-Lapalme, A., Sowa, A., Delfrate, J., Tastet, O., Corbin, D., Kulbay, M., Ozdemir, D., Noël, M.-J., Marois-Blanchet, F.-C., Harvey, F., et al. (2026) · European Heart Journal

ECG Monitoring and AnalysisMachine Learning in Healthcare

Cited by 20

Natural language processing to adjudicate heart failure hospitalizations in global clinical trials

Marti-Castellote, P. M., Reeder, C., Claggett, B., Singh, P., Lau, E. S., Khurshid, S., Batra, P., Lubitz, S. A., Maddah, M., Vardeny, O., et al. (2025) · Circulation: Heart Failure

Artificial Intelligence in HealthcareHeart Failure Treatment and Management

Cited by 14

Artificial Intelligence-Enabled ECG Analysis to Predict Incident Heart Failure

Khurshid, S., Friedman, S. F., Kany, S., D’Souza, V., Roshandelpoor, A., Kosyakovsky, L. B., Chitsazan, M., Cunningham, J. W., Singh, P., Lau, E. S., et al. (2026) · Circulation: Heart Failure

ECG Monitoring and AnalysisArtificial Intelligence in Healthcare

Cited by 2