A deep learning algorithm to detect anaemia with ECGs: a retrospective, multicentre study.

Journal: The Lancet. Digital health
PMID: 33328095

Abstract

BACKGROUND: Anaemia is an important health-care burden globally, and screening for anaemia is crucial to prevent multi-organ injury, irreversible complications, and life-threatening adverse events. We aimed to establish whether a deep learning algorithm (DLA) that enables non-invasive anaemia screening from electrocardiograms (ECGs) might improve the detection of anaemia.

Authors

  • Joon-Myoung Kwon
    Department of Emergency Medicine, Mediplex Sejong Hospital, Incheon, Korea.
  • Younghoon Cho
    Medical Research and Development Center, Bodyfriend, Seoul, South Korea.
  • Ki-Hyun Jeon
    Department of Cardiology, Cardiovascular Center, Mediplex Sejong Hospital, Incheon, Korea.
  • Soohyun Cho
    Medical Research and Development Center, Bodyfriend, Seoul, South Korea.
  • Kyung-Hee Kim
    Department of Cardiology, Cardiovascular Center, Mediplex Sejong Hospital, Incheon, Korea.
  • Seung Don Baek
    Division of Nephrology, Department of Internal Medicine, Mediplex Sejong Hospital, Incheon, South Korea.
  • Soomin Jeung
    Division of Nephrology, Department of Internal Medicine, Mediplex Sejong Hospital, Incheon, South Korea.
  • Jinsik Park
    Department of Cardiology, Mediplex Sejong Hospital, Incheon, Korea.
  • Byung-Hee Oh
    Division of Cardiology, Cardiovascular Center, Mediplex Sejong Hospital, Incheon, Republic of Korea.

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