Al-Mallah, Mouaz H.

Machine learning for prediction of all-cause mortality in patients with suspected coronary artery disease: a 5-year multicentre prospective registry analysis

Motwani, M., Dey, D., Berman, D. S., Germano, G., Achenbach, S., Al-Mallah, M. H., Andreini, D., Budoff, M. J., Cademartiri, F., Callister, T. Q., et al. (2016) · European Heart Journal

Cardiac Imaging and DiagnosticsArtificial Intelligence in Healthcare

Cited by 692

Public Availability of Published Research Data in High-Impact Journals

Alsheikh-Ali, A. A., Qureshi, W., Al-Mallah, M. H., & Ioannidis, J. P. A. (2011) · PLoS ONE

Research Data Management PracticesAcademic Publishing and Open Access

Cited by 363

Long-Term All-Cause and Cause-Specific Mortality in Asymptomatic Patients With CAC ≥1,000

Peng, A. W., Mirbolouk, M., Orimoloye, O. A., Osei, A. D., Dardari, Z., Dzaye, O., Budoff, M. J., Shaw, L., Miedema, M. D., Rumberger, J., et al. (2020) · JACC: Cardiovascular Imaging

Cardiac Imaging and DiagnosticsHealthcare Systems and Public Health

Cited by 134

Does coronary CT angiography improve risk stratification over coronary calcium scoring in symptomatic patients with suspected coronary artery disease? Results from the prospective multicenter international CONFIRM registry

Al-Mallah, M. H., Qureshi, W., Lin, F. Y., Achenbach, S., Berman, D. S., Budoff, M. J., Callister, T. Q., Chang, H.-J., Cademartiri, F., Chinnaiyan, K., et al. (2014) · European Heart Journal - Cardiovascular Imaging

Cardiac Imaging and DiagnosticsCoronary Interventions and Diagnostics

Cited by 125

Cardiorespiratory fitness and incident diabetes: the FIT (Henry Ford Exercise Testing) project.

Juraschek, S. P., Blaha, M. J., Blumenthal, R. S., Brawner, C., Qureshi, W., Keteyian, S. J., Schairer, J., Ehrman, J. K., & Al-Mallah, M. H. (2015) · Diabetes Care

Physical Activity and HealthDiabetes, Cardiovascular Risks, and Lipoproteins

Cited by 71

Relation of resting heart rate to risk for all-cause mortality by gender after considering exercise capacity (the Henry Ford Exercise Testing Project)

Aladin, A. I., Whelton, S. P., Al-Mallah, M. H., Blaha, M. J., Keteyian, S. J., Juraschek, S. P., Rubin, J., Brawner, C. A., & Michos, E. D. (2014) · The American Journal of Cardiology

Cardiovascular and exercise physiologyHeart rate and cardiovascular health

Cited by 70

Fitness, Fatness, and Mortality: The FIT (Henry Ford Exercise Testing) Project

McAuley, P. A., Blaha, M. J., Keteyian, S. J., Brawner, C. A., Al Rifai, M., Dardari, Z. A., Ehrman, J. K., & Al-Mallah, M. H. (2016) · The American Journal of Medicine

Cardiovascular and exercise physiologyPhysical Activity and Health

Cited by 41

Coronary atherosclerosis scoring with semiquantitative CCTA risk scores for prediction of major adverse cardiac events: propensity score-based analysis of diabetic and non-diabetic patients

van den Hoogen, I. J., van Rosendael, A. R., Lin, F. Y., Lu, Y., Dimitriu-Leen, A. C., Smit, J. M., Scholte, A. J. H. A., Achenbach, S., Al-Mallah, M. H., Andreini, D., et al. (2020) · Journal of Cardiovascular Computed Tomography

Cardiac Imaging and DiagnosticsCoronary Interventions and Diagnostics

Cited by 31

Tracking the Preclinical Progression of Transthyretin Amyloid Cardiomyopathy Using Artificial Intelligence-Enabled Electrocardiography and Echocardiography

Oikonomou, E. K., Sangha, V., Vasisht Shankar, S., Coppi, A., Krumholz, H. M., Nasir, K., Miller, E. J., Gallegos-Kattan, C., Al-Mallah, M. H., Al-Kindi, S., et al. (2024) · medRxiv

Amyloidosis: Diagnosis, Treatment, OutcomesArtificial Intelligence in Healthcare and Education

Cited by 7