Time and event-specific deep learning for personalized risk assessment after cardiac perfusion imaging

Standard clinical interpretation of myocardial perfusion imaging (MPI) has proven prognostic value for predicting major adverse cardiovascular events (MACE). However, personalizing predictions to a specific event type and time interval is more challenging. We demonstrate an explainable deep learning...

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Main Authors: Bateman, T.M (Author), Berman, D.S (Author), Dey, D. (Author), Di Carli, M. (Author), Dorbala, S. (Author), Einstein, A.J (Author), Fish, M.B (Author), Hauser, M.T (Author), Kaufmann, P.A (Author), Kwieciński, J. (Author), Liang, J.X (Author), Miller, E.J (Author), Miller, R.J.H (Author), Motwani, M. (Author), Pieszko, K. (Author), Ruddy, T.D (Author), Shanbhag, A.D (Author), Sharir, T. (Author), Singh, A. (Author), Sinusas, A.J (Author), Slomka, P.J (Author)
Format: Article
Language:English
Published: Nature Research 2023
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