Recent advancements and applications of deep learning in heart failure: Α systematic review.

Journal: Computers in biology and medicine
Published Date: May 6, 2024

Abstract

BACKGROUND: Heart failure (HF), a global health challenge, requires innovative diagnostic and management approaches. The rapid evolution of deep learning (DL) in healthcare necessitates a comprehensive review to evaluate these developments and their potential to enhance HF evaluation, aligning clinical practices with technological advancements.

Authors

  • Georgios Petmezas
    2nd Department of Obstetrics and Gynecology, Medical School, Aristotle University of Thessaloniki, Thessaloniki, Greece; Centre for Research and Technology Hellas, Thessaloniki, Greece. Electronic address: petmezgs@auth.gr.
  • Vasileios E Papageorgiou
    Department of Mathematics, Aristotle University of Thessaloniki, Thessaloniki, Greece.
  • Vasileios Vassilikos
    3rd Department of Cardiology, Medical School, Aristotle University of Thessaloniki, Thessaloniki, Greece.
  • Efstathios Pagourelias
    3rd Department of Cardiology, Medical School, Aristotle University of Thessaloniki, Thessaloniki, Greece.
  • George Tsaklidis
    Department of Mathematics, Aristotle University of Thessaloniki, Thessaloniki, Greece.
  • Aggelos K Katsaggelos
    Department of Electrical and Computer Engineering, McCormick School of Engineering and Applied Science, Northwestern University, Evanston, Illinois.
  • Nicos Maglaveras

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