Robert J.H. Miller

Deep Learning–Based Quantification of Epicardial Adipose Tissue Volume and Attenuation Predicts Major Adverse Cardiovascular Events in Asymptomatic Subjects

Evann Eisenberg, Priscilla McElhinney, Frédéric Commandeur et al. · Circulation Cardiovascular Imaging · 2020 · 151 citations · Full text

Machine learning to predict the long-term risk of myocardial infarction and cardiac death based on clinical risk, coronary calcium, and epicardial adipose tissue: a prospective study

Frédéric Commandeur, Piotr J. Slomka, Markus Goeller et al. · Cardiovascular Research · 2019 · 137 citations · Full text

Clinical Deployment of Explainable Artificial Intelligence of SPECT for Diagnosis of Coronary Artery Disease

Yuka Otaki, Ananya Singh, Paul Kavanagh et al. · JACC. Cardiovascular imaging · 2021 · 107 citations · Full text

Artificial Intelligence, Clinical Innovation, Health Sciences +15

Deep Learning of Coronary Calcium Scores From PET/CT Attenuation Maps Accurately Predicts Adverse Cardiovascular Events

Konrad Pieszko, Aakash Shanbhag, Aditya Killekar et al. · JACC. Cardiovascular imaging · 2022 · 69 citations

Computed Tomography, Engineering, Machine Learning +12

Prognostically safe stress-only single-photon emission computed tomography myocardial perfusion imaging guided by machine learning: report from REFINE SPECT

Lien-Hsin Hu, Robert J.H. Miller, Tali Sharir et al. · European Heart Journal - Cardiovascular Imaging · 2020 · 63 citations