Schoepf, U. Joseph

Clinical applications of machine learning in cardiovascular disease and its relevance to cardiac imaging

Al’Aref, S. J., Anchouche, K., Singh, G., Slomka, P. J., Kolli, K. K., Kumar, A., Pandey, M., Maliakal, G., van Rosendael, A. R., Beecy, A. N., et al. (2019) · European Heart Journal

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Coronary Artery Disease - Reporting and Data System (CAD-RADS)

Cury, R. C., Abbara, S., Achenbach, S., Agatston, A., Berman, D. S., Budoff, M. J., Dill, K. E., Jacobs, J. E., Maroules, C. D., Rubin, G. D., et al. (2016) · JACC: Cardiovascular Imaging

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Evaluation of a Deep Learning–Based Automated CT Coronary Artery Calcium Scoring Algorithm

Martin, S. S., van Assen, M., Rapaka, S., Hudson, H. T., Fischer, A. M., Varga-Szemes, A., Sahbaee, P., Schwemmer, C., Gulsun, M. A., Cimen, S., et al. (2020) · JACC: Cardiovascular Imaging

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Prognostic implications of coronary CT angiography-derived quantitative markers for the prediction of major adverse cardiac events

Tesche, C., Plank, F., De Cecco, C. N., Duguay, T. M., Albrecht, M. H., Varga-Szemes, A., Bayer, R. R., Yang, J., Jacks, I. L., Gramer, B. M., et al. (2016) · Journal of Cardiovascular Computed Tomography

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The power and limitations of machine learning and artificial intelligence in cardiac CT

Varga-Szemes, A., Jacobs, B. E., & Schoepf, U. J. (2018) · Journal of Cardiovascular Computed Tomography

Artificial Intelligence in Healthcare and EducationCardiac Imaging and Diagnostics

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