Identifying pediatric heart murmurs and distinguishing innocent from pathologic using deep learning.

Journal: Artificial intelligence in medicine
PMID: 38723434

Abstract

OBJECTIVE: To develop a deep learning algorithm to perform multi-class classification of normal pediatric heart sounds, innocent murmurs, and pathologic murmurs.

Authors

  • George Zhou
    Laboratory of Systems Pharmacology, Harvard Program in Therapeutic Science, Harvard Medical School, Boston, MA, USA.
  • Candace Chien
    Children's Hospital Los Angeles, Los Angeles, CA 90027, USA.
  • Justin Chen
    Staten Island University Hospital, Northwell Health, Staten Island, NY 10305, USA.
  • Lucille Luan
    Teachers College, Columbia University, New York, NY 10027, USA.
  • Yunchan Chen
    Weill Cornell Medicine, New York, NY 10021, USA.
  • Sheila Carroll
    Division of Pediatric Cardiology, NewYork-Presbyterian Hospital, New York, NY 10021, USA.
  • Jeffrey Dayton
    Division of Pediatric Cardiology, NewYork-Presbyterian Hospital, New York, NY 10021, USA.
  • Maria Thanjan
    Division of Pediatric Cardiology, NewYork-Presbyterian Hospital Queens, New York, NY 11355, USA.
  • Ken Bayle
    Division of Pediatric Cardiology, NewYork-Presbyterian Hospital Queens, New York, NY 11355, USA.
  • Patrick Flynn
    Division of Pediatric Cardiology, NewYork-Presbyterian Hospital, New York, NY 10021, USA.

Keywords

External Resources

Popular Topics
Recent Journals