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Artificial intelligence in preventive cardiology.
El Sherbini, Adham; Rosenson, Robert S; Al Rifai, Mahmoud; Virk, Hafeez Ul Hassan; Wang, Zhen; Virani, Salim; Glicksberg, Benjamin S; Lavie, Carl J; Krittanawong, Chayakrit.
Afiliación
  • El Sherbini A; Faculty of Health Sciences, Queen's University, Kingston, ON, Canada.
  • Rosenson RS; Cardiometabolics Unit, Mount Sinai Hospital, Mount Sinai Heart, NY, United States of America.
  • Al Rifai M; Houston Methodist DeBakey Heart & Vascular Center, Houston, TX, United States of America.
  • Virk HUH; Harrington Heart & Vascular Institute, Case Western Reserve University, University Hospitals Cleveland Medical Center, Cleveland, OH, United States of America.
  • Wang Z; Robert D. and Patricia E. Kern Center for the Science of Health Care Delivery, Mayo Clinic, Rochester, MN, United States of America; Division of Health Care Policy and Research, Department of Health Sciences Research, Mayo Clinic, Rochester, MN, United States of America.
  • Virani S; Section of Cardiology, The Aga Khan University, Texas Heart Institute, Baylor College of Medicine, Houston, TX, United States of America.
  • Glicksberg BS; The Hasso Plattner Institute for Digital Health, Icahn School of Medicine at Mount Sinai, New York, NY, United States of America.
  • Lavie CJ; John Ochsner Heart and Vascular Institute, Ochsner Clinical School, The University of Queensland School of Medicine, New Orleans, LA, USA.
  • Krittanawong C; Cardiology Division, NYU Langone Health and NYU School of Medicine, New York, NY, United States of America. Electronic address: Chayakrit.krittanawong@va.gov.
Prog Cardiovasc Dis ; 84: 76-89, 2024.
Article en En | MEDLINE | ID: mdl-38460897
ABSTRACT
Artificial intelligence (AI) is a field of study that strives to replicate aspects of human intelligence into machines. Preventive cardiology, a subspeciality of cardiovascular (CV) medicine, aims to target and mitigate known risk factors for CV disease (CVD). AI's integration into preventive cardiology may introduce novel treatment interventions and AI-centered clinician assistive tools to reduce the risk of CVD. AI's role in nutrition, weight loss, physical activity, sleep hygiene, blood pressure, dyslipidemia, smoking, alcohol, recreational drugs, and mental health has been investigated. AI has immense potential to be used for the screening, detection, and monitoring of the mentioned risk factors. However, the current literature must be supplemented with future clinical trials to evaluate the capabilities of AI interventions for preventive cardiology. This review discusses present examples, potentials, and limitations of AI's role for the primary and secondary prevention of CVD.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Prevención Primaria / Inteligencia Artificial / Cardiología / Enfermedades Cardiovasculares / Factores de Riesgo de Enfermedad Cardiaca Límite: Humans Idioma: En Revista: Prog Cardiovasc Dis Año: 2024 Tipo del documento: Article País de afiliación: Canadá Pais de publicación: Estados Unidos
Texto completo
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Prevención Primaria / Inteligencia Artificial / Cardiología / Enfermedades Cardiovasculares / Factores de Riesgo de Enfermedad Cardiaca Límite: Humans Idioma: En Revista: Prog Cardiovasc Dis Año: 2024 Tipo del documento: Article País de afiliación: Canadá Pais de publicación: Estados Unidos