Flamm, Scott D

A novel machine learning-derived radiotranscriptomic signature of perivascular fat improves cardiac risk prediction using coronary CT angiography

Oikonomou, E. K., Williams, M. C., Kotanidis, C. P., Desai, M. Y., Marwan, M., Antonopoulos, A. S., Thomas, K. E., Thomas, S., Akoumianakis, I., Fan, L. M., et al. (2019) · European Heart Journal

Cardiovascular Disease and AdiposityRadiomics and Machine Learning in Medical Imaging

Cited by 534

Redistribution of regional and organ blood volume and effect on cardiac function in relation to upright exercise intensity in healthy human subjects

Flamm, S. D., Taki, J., Moore, R., Lewis, S. F., Keech, F., Maltais, F., Ahmad, M., Callahan, R., Dragotakes, S., & Alpert, N. (1990) · Circulation

Cardiovascular and exercise physiologyCardiovascular Effects of Exercise

Cited by 201

ACR appropriateness criteria® imaging of mesenteric ischemia

Oliva, I. B., Davarpanah, A. H., Rybicki, F. J., Desjardins, B., Flamm, S. D., Francois, C. J., Gerhard-Herman, M. D., Kalva, S. P., Ashraf Mansour, M., Mohler, E. R., et al. (2013) · Abdominal Imaging

Abdominal vascular conditions and treatmentsOmental and Epiploic Conditions

Cited by 200