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The potential of artificial intelligence to revolutionize health care delivery, research, and education in cardiac electrophysiology.
Al-Khatib, Sana M; Singh, Jagmeet P; Ghanbari, Hamid; McManus, David D; Deering, Thomas F; Avari Silva, Jennifer N; Mittal, Suneet; Krahn, Andrew; Hurwitz, Jodie L.
Afiliación
  • Al-Khatib SM; Duke Clinical Research Institute, Division of Cardiology, Department of Medicine, Duke University School of Medicine, Durham, North Carolina. Electronic address: sana.alkhatib@duke.edu.
  • Singh JP; Cardiology Division, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts.
  • Ghanbari H; Department of Internal Medicine, Division of Cardiovascular Medicine, University of Michigan Medical School, Ann Arbor, Michigan.
  • McManus DD; Department of Medicine, University of Massachusetts Chan Medical School and UMass Memorial Health, Boston, Massachusetts.
  • Deering TF; Piedmont Heart of Buckhead Electrophysiology, Piedmont Heart Institute, Atlanta, Georgia.
  • Avari Silva JN; Division of Pediatric Cardiology, Washington University School of Medicine, Department of Biomedical Engineering, Washington University in St. Louis, St. Louis, Missouri.
  • Mittal S; Valley Health System, Paramus, New Jersey.
  • Krahn A; Division of Cardiology, University of British Columbia, Vancouver, British Columbia, Canada.
  • Hurwitz JL; North Texas Heart Center, Dallas, Texas.
Heart Rhythm ; 21(6): 978-989, 2024 06.
Article en En | MEDLINE | ID: mdl-38752904
ABSTRACT
The field of electrophysiology (EP) has benefited from numerous seminal innovations and discoveries that have enabled clinicians to deliver therapies and interventions that save lives and promote quality of life. The rapid pace of innovation in EP may be hindered by several challenges including the aging population with increasing morbidity, the availability of multiple costly therapies that, in many instances, confer minor incremental benefit, the limitations of healthcare reimbursement, the lack of response to therapies by some patients, and the complications of the invasive procedures performed. To overcome these challenges and continue on a steadfast path of transformative innovation, the EP community must comprehensively explore how artificial intelligence (AI) can be applied to healthcare delivery, research, and education and consider all opportunities in which AI can catalyze innovation; create workflow, research, and education efficiencies; and improve patient outcomes at a lower cost. In this white paper, we define AI and discuss the potential of AI to revolutionize the EP field. We also address the requirements for implementing, maintaining, and enhancing quality when using AI and consider ethical, operational, and regulatory aspects of AI implementation. This manuscript will be followed by several perspective papers that will expand on some of these topics.
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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Inteligencia Artificial / Atención a la Salud / Electrofisiología Cardíaca Límite: Humans Idioma: En Revista: Heart Rhythm Año: 2024 Tipo del documento: Article

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Inteligencia Artificial / Atención a la Salud / Electrofisiología Cardíaca Límite: Humans Idioma: En Revista: Heart Rhythm Año: 2024 Tipo del documento: Article