Perez, Marco

Sequencing of 53,831 diverse genomes from the NHLBI TOPMed Program

Taliun, D., Harris, D. N., Kessler, M. D., Carlson, J., Szpiech, Z. A., Torres, R., Taliun, S. A. G., Corvelo, A., Gogarten, S. M., Kang, H. M., et al. (2021) · Nature

Genetic Associations and EpidemiologyGenomics and Rare Diseases

Cited by 2,213

Large-Scale Assessment of a Smartwatch to Identify Atrial Fibrillation

Perez, M. V., Mahaffey, K. W., Hedlin, H., Rumsfeld, J. S., Garcia, A., Ferris, T., Balasubramanian, V., Russo, A. M., Rajmane, A., Cheung, L., et al. (2019) · New England Journal of Medicine

Non-Invasive Vital Sign MonitoringAtrial Fibrillation Management and Outcomes

Cited by 1,917

2023 ACC/AHA/ACCP/HRS Guideline for the Diagnosis and Management of Atrial Fibrillation

Joglar, J. A., Chung, M. K., Armbruster, A. L., Benjamin, E. J., Chyou, J. Y., Cronin, E. M., Deswal, A., Eckhardt, L. L., Goldberger, Z. D., Gopinathannair, R., et al. (2024) · Journal of the American College of Cardiology

Atrial Fibrillation Management and OutcomesAcute Ischemic Stroke Management

Cited by 933

Inherited causes of clonal haematopoiesis in 97,691 whole genomes

Bick, A. G., Weinstock, J. S., Nandakumar, S. K., Fulco, C. P., Bao, E. L., Zekavat, S. M., Szeto, M. D., Liao, X., Leventhal, M. J., Nasser, J., et al. (2020) · Nature

Acute Myeloid Leukemia ResearchGenetic Associations and Epidemiology

Cited by 733

Rationale and design of a large-scale, app-based study to identify cardiac arrhythmias using a smartwatch: the apple heart study

Turakhia, M. P., Desai, M., Hedlin, H., Rajmane, A., Talati, N., Ferris, T., Desai, S., Nag, D., Patel, M., Kowey, P., et al. (2019) · American Heart Journal

Non-Invasive Vital Sign MonitoringAtrial Fibrillation Management and Outcomes

Cited by 474

p300/MDM2 complexes participate in MDM2-mediated p53 degradation

Grossman, S. R., Perez, M., Kung, A. L., Joseph, M., Mansur, C., Xiao, Z.-X., Kumar, S., Howley, P. M., & Livingston, D. M. (1998) · Molecular Cell

Cancer-related Molecular PathwaysHeat shock proteins research

Cited by 414

Deep Learning Electrocardiographic Analysis for Detection of Left-Sided Valvular Heart Disease

Elias, P., Poterucha, T. J., Rajaram, V., Moller, L. M., Rodriguez, V., Bhave, S., Hahn, R. T., Tison, G., Abreau, S. A., Barrios, J., et al. (2022) · Journal of the American College of Cardiology

ECG Monitoring and AnalysisArtificial Intelligence in Healthcare

Cited by 153

Whole Genome Sequence Analysis of the Plasma Proteome in Black Adults Provides Novel Insights Into Cardiovascular Disease

Katz, D. H., Tahir, U. A., Bick, A. G., Pampana, A., Ngo, D., Benson, M. D., Yu, Z., Robbins, J. M., Chen, Z.-Z., Cruz, D. E., et al. (2022) · Circulation

Genetic Associations and EpidemiologyGenetic Mapping and Diversity in Plants and Animals

Cited by 92

Multimodal deep learning enhances diagnostic precision in left ventricular hypertrophy

Soto, J. T., Weston Hughes, J., Sanchez, P. A., Perez, M., Ouyang, D., & Ashley, E. A. (2022) · European Heart Journal - Digital Health

Cardiomyopathy and Myosin StudiesArtificial Intelligence in Healthcare

Cited by 76

Artificial Intelligence in Cardiovascular Care—Part 2: Applications

Jain, S. S., Elias, P., Poterucha, T., Randazzo, M., Lopez Jimenez, F., Khera, R., Perez, M., Ouyang, D., Pirruccello, J., Salerno, M., et al. (2024) · Journal of the American College of Cardiology

Artificial Intelligence in Healthcare and EducationArtificial Intelligence in Healthcare

Cited by 74

Electrocardiographic deep learning for predicting post-procedural mortality: a model development and validation study

Ouyang, D., Theurer, J., Stein, N. R., Hughes, J. W., Elias, P., He, B., Yuan, N., Duffy, G., Sandhu, R. K., Ebinger, J., et al. (2024) · The Lancet Digital Health

ECG Monitoring and AnalysisCardiac, Anesthesia and Surgical Outcomes

Cited by 64

Race, Sex, and Age Disparities in the Performance of ECG Deep Learning Models Predicting Heart Failure

Kaur, D., Hughes, J. W., Rogers, A. J., Kang, G., Narayan, S. M., Ashley, E. A., & Perez, M. V. (2024) · Circulation: Heart Failure

Artificial Intelligence in HealthcareECG Monitoring and Analysis

Cited by 58

Whole-genome association analyses of sleep-disordered breathing phenotypes in the NHLBI TOPMed program

Cade, B. E., Lee, J., Sofer, T., Wang, H., Zhang, M., Chen, H., Gharib, S. A., Gottlieb, D. J., Guo, X., Lane, J. M., et al. (2021) · Genome Medicine

Obstructive Sleep Apnea ResearchGenetic Associations and Epidemiology

Cited by 33

Serum Potassium Monitoring Using AI-Enabled Smartwatch Electrocardiograms

Chiu, I.-M., Wu, P.-J., Zhang, H., Hughes, J. W., Rogers, A. J., Jalilian, L., Perez, M., Lin, C.-H. R., Lee, C.-T., Zou, J., et al. (2024) · JACC: Clinical Electrophysiology

ECG Monitoring and AnalysisPotassium and Related Disorders

Cited by 31

How Will Genetics Inform the Clinical Care of Atrial Fibrillation?

Shoemaker, M. B., Shah, R. L., Roden, D. M., & Perez, M. V. (2020) · Circulation Research

Atrial Fibrillation Management and OutcomesCardiac electrophysiology and arrhythmias

Cited by 27