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Artificial Intelligence for Cardiovascular Care-Part 1: Advances: JACC Review Topic of the Week.
Elias, Pierre; Jain, Sneha S; Poterucha, Timothy; Randazzo, Michael; Lopez Jimenez, Francisco; Khera, Rohan; Perez, Marco; Ouyang, David; Pirruccello, James; Salerno, Michael; Einstein, Andrew J; Avram, Robert; Tison, Geoffrey H; Nadkarni, Girish; Natarajan, Vivek; Pierson, Emma; Beecy, Ashley; Kumaraiah, Deepa; Haggerty, Chris; Avari Silva, Jennifer N; Maddox, Thomas M.
Afiliação
  • Elias P; Seymour, Paul and Gloria Milstein Division of Cardiology, Columbia University Irving Medical Center, New York, New York, USA; Department of Biomedical Informatics Columbia University Irving Medical Center, New York, New York, USA.
  • Jain SS; Division of Cardiology, Stanford University School of Medicine, Palo Alto, California, USA.
  • Poterucha T; Seymour, Paul and Gloria Milstein Division of Cardiology, Columbia University Irving Medical Center, New York, New York, USA.
  • Randazzo M; Division of Cardiology, University of Chicago Medical Center, Chicago, Illinois, USA.
  • Lopez Jimenez F; Department of Cardiology, Mayo Clinic College of Medicine, Rochester, Minnesota, USA.
  • Khera R; Division of Cardiology, Yale School of Medicine, New Haven, Connecticut, USA.
  • Perez M; Division of Cardiology, Stanford University School of Medicine, Palo Alto, California, USA.
  • Ouyang D; Division of Cardiology, Cedars-Sinai Medical Center, Los Angeles, California, USA.
  • Pirruccello J; Division of Cardiology, University of California-San Francisco, San Francisco, California, USA.
  • Salerno M; Division of Cardiology, Stanford University School of Medicine, Palo Alto, California, USA.
  • Einstein AJ; Seymour, Paul and Gloria Milstein Division of Cardiology, Columbia University Irving Medical Center, New York, New York, USA.
  • Avram R; Division of Cardiology, Montreal Heart Institute, Montreal, Quebec, Canada.
  • Tison GH; Division of Cardiology, University of California-San Francisco, San Francisco, California, USA.
  • Nadkarni G; Icahn School of Medicine at Mount Sinai, New York, New York, USA.
  • Natarajan V; Google Health, Mountain View, California, USA.
  • Pierson E; Department of Computer Science, Cornell Tech, New York, New York, USA.
  • Beecy A; NewYork-Presbyterian Health System, New York, New York, USA; Division of Cardiology, Weill Cornell Medical College, New York, New York, USA.
  • Kumaraiah D; Seymour, Paul and Gloria Milstein Division of Cardiology, Columbia University Irving Medical Center, New York, New York, USA; NewYork-Presbyterian Health System, New York, New York, USA.
  • Haggerty C; Department of Biomedical Informatics Columbia University Irving Medical Center, New York, New York, USA; NewYork-Presbyterian Health System, New York, New York, USA.
  • Avari Silva JN; Division of Cardiology, Washington University School of Medicine, St Louis, Missouri, USA.
  • Maddox TM; Division of Cardiology, Washington University School of Medicine, St Louis, Missouri, USA. Electronic address: thomas.maddox@bjc.org.
J Am Coll Cardiol ; 83(24): 2472-2486, 2024 Jun 18.
Article em En | MEDLINE | ID: mdl-38593946
ABSTRACT
Recent artificial intelligence (AI) advancements in cardiovascular care offer potential enhancements in diagnosis, treatment, and outcomes. Innovations to date focus on automating measurements, enhancing image quality, and detecting diseases using novel methods. Applications span wearables, electrocardiograms, echocardiography, angiography, genetics, and more. AI models detect diseases from electrocardiograms at accuracy not previously achieved by technology or human experts, including reduced ejection fraction, valvular heart disease, and other cardiomyopathies. However, AI's unique characteristics necessitate rigorous validation by addressing training methods, real-world efficacy, equity concerns, and long-term reliability. Despite an exponentially growing number of studies in cardiovascular AI, trials showing improvement in outcomes remain lacking. A number are currently underway. Embracing this rapidly evolving technology while setting a high evaluation benchmark will be crucial for cardiology to leverage AI to enhance patient care and the provider experience.
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Texto completo: 1 Bases de dados: MEDLINE Assunto principal: Inteligência Artificial / Doenças Cardiovasculares Limite: Humans Idioma: En Revista: J Am Coll Cardiol Ano de publicação: 2024 Tipo de documento: Article País de afiliação: Estados Unidos

Texto completo: 1 Bases de dados: MEDLINE Assunto principal: Inteligência Artificial / Doenças Cardiovasculares Limite: Humans Idioma: En Revista: J Am Coll Cardiol Ano de publicação: 2024 Tipo de documento: Article País de afiliação: Estados Unidos