Artificial intelligence in preventive cardiology

IF 5.6 2区医学 Q1 CARDIAC & CARDIOVASCULAR SYSTEMS

Progress in cardiovascular diseases Pub Date : 2024-05-01 DOI:10.1016/j.pcad.2024.03.002

Adham El Sherbini , Robert S. Rosenson , Mahmoud Al Rifai , Hafeez Ul Hassan Virk , Zhen Wang , Salim Virani , Benjamin S. Glicksberg , Carl J. Lavie , Chayakrit Krittanawong

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引用次数: 0

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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人工智能在预防性心脏病学中的应用。

人工智能（AI）是一个致力于将人类智能的各个方面复制到机器中的研究领域。预防心脏病学是心血管（CV）医学的一个分支专业，旨在针对并减轻已知的心血管疾病（CVD）风险因素。将人工智能融入预防性心脏病学可能会引入新的治疗干预措施和以人工智能为中心的临床医生辅助工具，以降低心血管疾病的风险。人工智能在营养、减肥、体育锻炼、睡眠卫生、血压、血脂异常、吸烟、饮酒、娱乐性药物和心理健康方面的作用已得到研究。人工智能在筛查、检测和监控上述危险因素方面具有巨大的潜力。然而，目前的文献必须通过未来的临床试验来补充，以评估人工智能干预在预防心脏病学方面的能力。本综述将讨论人工智能在心血管疾病一级和二级预防中的作用、潜力和局限性。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Progress in cardiovascular diseases 医学-心血管系统

CiteScore

10.90

自引率

6.60%

发文量

审稿时长

7 days

期刊介绍： Progress in Cardiovascular Diseases provides comprehensive coverage of a single topic related to heart and circulatory disorders in each issue. Some issues include special articles, definitive reviews that capture the state of the art in the management of particular clinical problems in cardiology.