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Proceedings of the NHLBI Workshop on Artificial Intelligence in Cardiovascular Imaging: Translation to Patient Care.
Dey, Damini; Arnaout, Rima; Antani, Sameer; Badano, Aldo; Jacques, Louis; Li, Huiqing; Leiner, Tim; Margerrison, Edward; Samala, Ravi; Sengupta, Partho P; Shah, Sanjiv J; Slomka, Piotr; Williams, Michelle C; Bandettini, W Patricia; Sachdev, Vandana.
Affiliation
  • Dey D; Cedars-Sinai Medical Center, Los Angeles, California, USA.
  • Arnaout R; Department of Medicine, University of California-San Francisco, San Francisco, California, USA. Electronic address: rima.arnaout@ucsf.edu.
  • Antani S; National Library of Medicine, National Institutes of Health, Bethesda, Maryland, USA.
  • Badano A; Office of Science and Engineering Laboratories, Center for Devices and Radiological Health, Food and Drug Administration, Silver Spring, Maryland, USA.
  • Jacques L; ADVI Health, LLC, Washington, DC, USA.
  • Li H; National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, Maryland, USA.
  • Leiner T; Mayo Clinic, Rochester, Minnesota, USA.
  • Margerrison E; Office of Science and Engineering Laboratories, Center for Devices and Radiological Health, Food and Drug Administration, Silver Spring, Maryland, USA.
  • Samala R; Office of Science and Engineering Laboratories, Center for Devices and Radiological Health, Food and Drug Administration, Silver Spring, Maryland, USA.
  • Sengupta PP; Department of Medicine, Rutgers University, Newark, New Jersey, USA.
  • Shah SJ; Department of Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA.
  • Slomka P; Cedars-Sinai Medical Center, Los Angeles, California, USA.
  • Williams MC; Centre for Cardiovascular Science, University of Edinburgh, Edinburgh, United Kingdom; British Heart Foundation Data Science Centre, London, United Kingdom.
  • Bandettini WP; National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, Maryland, USA.
  • Sachdev V; National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, Maryland, USA.
JACC Cardiovasc Imaging ; 16(9): 1209-1223, 2023 09.
Article in En | MEDLINE | ID: mdl-37480904
Artificial intelligence (AI) promises to revolutionize many fields, but its clinical implementation in cardiovascular imaging is still rare despite increasing research. We sought to facilitate discussion across several fields and across the lifecycle of research, development, validation, and implementation to identify challenges and opportunities to further translation of AI in cardiovascular imaging. Furthermore, it seemed apparent that a multidisciplinary effort across institutions would be essential to overcome these challenges. This paper summarizes the proceedings of the National Heart, Lung, and Blood Institute-led workshop, creating consensus around needs and opportunities for institutions at several levels to support and advance research in this field and support future translation.
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Artificial Intelligence / Cardiovascular System Limits: Humans Country/Region as subject: America do norte Language: En Journal: JACC Cardiovasc Imaging Journal subject: ANGIOLOGIA / CARDIOLOGIA / DIAGNOSTICO POR IMAGEM Year: 2023 Type: Article Affiliation country: United States
Fulltext
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PubMed Links
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Artificial Intelligence / Cardiovascular System Limits: Humans Country/Region as subject: America do norte Language: En Journal: JACC Cardiovasc Imaging Journal subject: ANGIOLOGIA / CARDIOLOGIA / DIAGNOSTICO POR IMAGEM Year: 2023 Type: Article Affiliation country: United States