Algorithm for predicting valvular heart disease from heart sounds in an unselected cohort.

Journal: Frontiers in cardiovascular medicine
Published Date: Jan 24, 2024

Abstract

OBJECTIVE: This study aims to assess the ability of state-of-the-art machine learning algorithms to detect valvular heart disease (VHD) from digital heart sound recordings in a general population that includes asymptomatic cases and intermediate stages of disease progression.

Authors

  • Per Niklas Waaler
    Department of Computer Science, UiT The Arctic University of Norway, Tromsø, Norway.
  • Hasse Melbye
    General Practice Research Unit, Department of Community Medicine, UiT The Arctic University of Norway, Tromsø, Norway.
  • Henrik Schirmer
    Department of Cardiology, Akershus University Hospital, Oslo, Norway.
  • Markus Kreutzer Johnsen
    Medsensio AS, Oslo, Norway.
  • Tom Donnem
    Department of Clinical Medicine, UiT The Arctic University of Norway, Tromsø, Norway.
  • Johan Ravn
    Medsensio AS, Oslo, Norway.
  • Stian Andersen
    General Practice Research Unit, Department of Community Medicine, UiT The Arctic University of Norway, Tromsø, Norway.
  • Anne Herefoss Davidsen
    General Practice Research Unit, Department of Community Medicine, UiT The Arctic University of Norway, Tromsø, Norway.
  • Juan Carlos Aviles Solis
    General Practice Research Unit, Department of Community Medicine, UiT The Arctic University of Norway, Tromsø, Norway.
  • Michael Stylidis
    Sørbyen Legesenter, Tromsø, Norway.
  • Lars Ailo Bongo
    Department of Computer Science, UiT The Arctic University of Norway, Tromsø, Norway.

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