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Artificial Intelligence in Congenital Heart Disease: Current State and Prospects.
Jone, Pei-Ni; Gearhart, Addison; Lei, Howard; Xing, Fuyong; Nahar, Jai; Lopez-Jimenez, Francisco; Diller, Gerhard-Paul; Marelli, Ariane; Wilson, Laura; Saidi, Arwa; Cho, David; Chang, Anthony C.
Afiliação
  • Jone PN; Section of Pediatric Cardiology, Department of Pediatrics, Lurie Children's Hospital of Chicago, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA.
  • Gearhart A; Department of Cardiology, Boston Children's Hospital and Harvard Medical School, Boston, Massachusetts, USA.
  • Lei H; Division of Pediatric Cardiology, Children's Hospital of Orange County, Orange, California, USA.
  • Xing F; Department of Biostatistics and Informatics, University of Colorado Anschutz Medical Campus, Aurora, Colorado, USA.
  • Nahar J; Department of Cardiology, Children's National Hospital, Washington, DC, USA.
  • Lopez-Jimenez F; Department of Cardiovascular Medicine, Mayo Clinic, Rochester, Minnesota, USA.
  • Diller GP; Department of Cardiology III-Adult Congenital and Valvular Heart Disease, University Hospital Muenster, Muenster, Germany.
  • Marelli A; Adult Congenital Heart Centre and National Centre for Pulmonary Hypertension, Royal Brompton and Harefield National Health Service Foundation Trust, Imperial College London, London, UK.
  • Wilson L; National Register for Congenital Heart Defects, Berlin, Germany.
  • Saidi A; McGill Adult Unit for Congenital Heart Disease Excellence, Department of Medicine, McGill University, Montréal, Québec, Canada.
  • Cho D; Department of Pediatrics, University of Florida-Congenital Heart Center, Gainesville, Florida, USA.
  • Chang AC; Department of Pediatrics, University of Florida-Congenital Heart Center, Gainesville, Florida, USA.
JACC Adv ; 1(5): 100153, 2022 Dec.
Article em En | MEDLINE | ID: mdl-38939457
ABSTRACT
The current era of big data offers a wealth of new opportunities for clinicians to leverage artificial intelligence to optimize care for pediatric and adult patients with a congenital heart disease. At present, there is a significant underutilization of artificial intelligence in the clinical setting for the diagnosis, prognosis, and management of congenital heart disease patients. This document is a call to action and will describe the current state of artificial intelligence in congenital heart disease, review challenges, discuss opportunities, and focus on the top priorities of artificial intelligence-based deployment in congenital heart disease.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: JACC Adv Ano de publicação: 2022 Tipo de documento: Article
Texto completo
Imprimir
XML
PubMed Links
Buscar no Google

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: JACC Adv Ano de publicação: 2022 Tipo de documento: Article