Detection of cardiac amyloidosis using machine learning on routine echocardiographic measurements.

Journal: Open heart
PMID: 39694574

Abstract

BACKGROUND: Cardiac amyloidosis (CA) is an underdiagnosed, progressive and lethal disease. Machine learning applied to common measurements derived from routine echocardiogram studies can inform suspicion of CA.

Authors

  • Rachel Si-Wen Chang
    UCSF, San Francisco, California, USA.
  • I-Min Chiu
    Department of Emergency Medicine, Kaohsiung Chang Gung Memorial Hospital, Chang Gung University College of Medicine, Kaohsiung, Taiwan.
  • Phillip Tacon
    Cedars-Sinai Medical Center, Los Angeles, California, USA.
  • Michael Abiragi
    Cedars-Sinai Medical Center, Los Angeles, California, USA.
  • Louie Cao
    Cedars-Sinai Medical Center, Los Angeles, California, USA.
  • Gloria Hong
    Cedars-Sinai Medical Center, Los Angeles, California, USA.
  • Jonathan Le
    Departments of1Neurosurgery and.
  • James Zou
    Department of Biomedical Data Science, Stanford University, Stanford, California.
  • Chathuri Daluwatte
    Alexion Pharmaceuticals, Boston, Massachusetts, USA.
  • Piero Ricchiuto
    Alexion Pharmaceuticals, Boston, Massachusetts, USA.
  • David Ouyang
    Division of Artificial Intelligence, Department of Medicine, Cedars-Sinai Medical Center, Los Angeles, California, USA.

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