Deep Learning to Estimate Cardiovascular Risk From Chest Radiographs : A Risk Prediction Study.

Journal: Annals of internal medicine
PMID: 38527287

Abstract

BACKGROUND: Guidelines for primary prevention of atherosclerotic cardiovascular disease (ASCVD) recommend a risk calculator (ASCVD risk score) to estimate 10-year risk for major adverse cardiovascular events (MACE). Because the necessary inputs are often missing, complementary approaches for opportunistic risk assessment are desirable.

Authors

  • Jakob Weiss
    Artificial Intelligence in Medicine (AIM) Program, Mass General Brigham, Harvard Medical School, Boston, MA, USA.
  • Vineet K Raghu
    Department of Computer Science, University of Pittsburgh, Pittsburgh, PA, USA.
  • Kaavya Paruchuri
    Cardiovascular Research Center and Center for Genomic Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, and Program in Medical and Population Genetics and Cardiovascular Disease Initiative, Broad Institute of Harvard and MIT, Cambridge, Massachusetts (K.P., P.N.).
  • Aniket Zinzuwadia
    Harvard Medical School, Boston, Massachusetts, USA.
  • Pradeep Natarajan
    Program in Medical and Population Genetics and Cardiovascular Disease Initiative, Broad Institute of MIT and Harvard, Cambridge, MA (S.M.Z., V.K.R., M.T., S.K., M.C.H., Z.Y., A.P., S.U., P.T.E., P.N.).
  • Hugo J W L Aerts
    Department of Radiation Oncology, Brigham and Women's Hospital, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, United States.
  • Michael T Lu
    Cardiovascular Imaging Research Center, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston.

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