AI-enabled cardiac chambers volumetry in coronary artery calcium scans (AI-CAC) predicts heart failure and outperforms NT-proBNP: The multi-ethnic study of Atherosclerosis.

Abstract

Authors

• Morteza Naghavi
  2 Society for Heart Attack Prevention and Eradication Palo Alto CA.
• Anthony Reeves
  Department of Computer Engineering, Cornell University, Ithaca, NY, USA.
• Matthew Budoff
  4 Division of Cardiology Los Angeles Biomedical Research at Harbor-UCLA Medical Center Torrance CA.
• Dong Li
  Department of Cardiovascular Medicine, Lanzhou University Second Hospital, 730030 Lanzhou, Gansu, China.
• Kyle Atlas
  HeartLung.AI, Houston, TX, USA.
• Chenyu Zhang
  Academy of Clinical Medicine, Guizhou Medical University, Guiyang 550004, China.
• Thomas Atlas
  Tustin Teleradiology, Tustin, CA, USA.
• Sion K Roy
  The Lundquist Institute, Torrance, CA, USA.
• Claudia I Henschke
  Department of Radiology, Icahn School of Medicine at Mount Sinai, New York.
• Nathan D Wong
  Department of Medicine, University of California at Irvine, CA (N.D.W.).
• Christopher deFilippi
  From the Center for Computational Health, IBM Research, T.J. Watson Research Center, Cambridge, MA (K.N.); Cardiovascular Wellness, Geisinger Health System, Danville, PA (S.R.S.); Digital Medicine, Scripps Health, San Diego, CA (S.R.S.); Cardiology, Inova Heart and Vascular Institute, Fairfax, VA (C.d.); Center for Computational Health, IBM Research, T.J. Watson Research Center, Yorktown Heights, NY (S.D.); and Research, Sutter Health Research, Walnut Creek, CA (W.F.S.).
• Daniel Levy
  The Framingham Heart Study, Framingham, MA 01701, USA.
• David F Yankelevitz
  Department of Radiology, Icahn School of Medicine at Mount Sinai, New York.

Keywords

External Resources