Handling missing values in machine learning to predict patient-specific risk of adverse cardiac events: Insights from REFINE SPECT registry. - Richard Ríos; Robert J. H. Miller; Nipun Manral; Tali Sharir; Andrew J. Einstein; Mathews Fish; Terrence D. Ruddy; Philipp A. Kaufmann; Albert J. Sinusas; Edward J. Miller; Timothy M. Bateman; Sharmila Dorbala; et al. (Comput. Biol. Medicine, 2022)

Time and event-specific deep learning for personalized risk assessment after cardiac perfusion imaging. - Konrad Pieszko; Aakash D. Shanbhag; Ananya Singh; M. Timothy Hauser; Robert J. H. Miller; Joanna X. Liang; Manish Motwani; Jacek Kwiecinski; Tali Sharir; Andrew J. Einstein; Mathews Fish; Terrence D. Ruddy; et al. (npj Digit. Medicine, 2023)

AI-derived epicardial fat measurements improve cardiovascular risk prediction from myocardial perfusion imaging. - Robert J. H. Miller; Aakash D. Shanbhag; Aditya Killekar; Mark Lemley; Bryan P. Bednarski; Serge D. Van Kriekinge; Paul Kavanagh; Attila Feher; Edward J. Miller; Andrew J. Einstein; Terrence D. Ruddy; Joanna X. Liang; et al. (npj Digit. Medicine, 2024)

Holistic AI analysis of hybrid cardiac perfusion images for mortality prediction. - Anna M. Marcinkiewicz; Wenhao Zhang; Aakash D. Shanbhag; Robert J. H. Miller; Mark Lemley; Giselle Ramirez; Mikolaj Buchwald; Aditya Killekar; Paul Kavanagh; Attila Feher; Edward J. Miller; Andrew J. Einstein; et al. (npj Digit. Medicine, 2025)