N. Manral

Artificial Intelligence-based quantification of atherosclerotic plaque and stenosis from coronary computed tomography angiography using a novel method

D. Dey, S. Achenbach, M. Dweck, 2022, Medical Imaging.

Machine Learning From Quantitative Coronary Computed Tomography Angiography Predicts Fractional Flow Reserve–Defined Ischemia and Impaired Myocardial Blood Flow

M. Motwani, D. Dey, P. Slomka, 2022, Circulation. Cardiovascular imaging.

Deep learning-enabled coronary CT angiography for plaque and stenosis quantification and cardiac risk prediction: an international multicentre study

D. Dey, S. Achenbach, H. Gransar, 2022, The Lancet. Digital health.

Deep learning-based plaque quantification from coronary computed tomography angiography: external validation and comparison with intravascular ultrasound

D. Dey, S. Achenbach, M. Dweck, 2021, European Heart Journal.

Handling missing values in machine learning to predict patient-specific risk of adverse cardiac events: Insights from REFINE SPECT registry

D. Dey, D. Berman, P. Kaufmann, 2022, Comput. Biol. Medicine.

Deep Learning From Coronary Computed Tomography Angiography for Atherosclerotic Plaque and Stenosis Quantification and Cardiac Risk Prediction

D. Dey, D. Berman, S. Achenbach, 2021, SSRN Electronic Journal.

Direct head-to-head comparison of convolutional long short-term memory and transformer networks for artificial Intelligence-based quantification of atherosclerotic plaque and stenosis from coronary CT angiography

D. Dey, P. Slomka, M. Dweck, 2023, Medical Imaging.