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人工智能改善心血管疾病人群健康状况。

Artificial intelligence to improve cardiovascular population health.

作者信息

Meder Benjamin, Asselbergs Folkert W, Ashley Euan

机构信息

Precision Digital Health and Informatics for Life, Clinic of Cardiology, Angiology and Pulmonology, University of Heidelberg, Im Neuenheimer Feld 410, Heidelberg 69120, Germany.

German Center for Cardiovascular Research (DZHK) Partnerside Heidelberg, Heidelberg, Germany.

出版信息

Eur Heart J. 2025 May 21;46(20):1907-1916. doi: 10.1093/eurheartj/ehaf125.

DOI:10.1093/eurheartj/ehaf125
PMID:40106837
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12093147/
Abstract

With the advent of artificial intelligence (AI), novel opportunities arise to revolutionize healthcare delivery and improve population health. This review provides a state-of-the-art overview of recent advancements in AI technologies and their applications in enhancing cardiovascular health at the population level. From predictive analytics to personalized interventions, AI-driven approaches are increasingly being utilized to analyse vast amounts of healthcare data, uncover disease patterns, and optimize resource allocation. Furthermore, AI-enabled technologies such as wearable devices and remote monitoring systems facilitate continuous cardiac monitoring, early detection of diseases, and promise more timely interventions. Additionally, AI-powered systems aid healthcare professionals in clinical decision-making processes, thereby improving accuracy and treatment effectiveness. By using AI systems to augment existing data sources, such as registries and biobanks, completely new research questions can be addressed to identify novel mechanisms and pharmaceutical targets. Despite this remarkable potential of AI in enhancing population health, challenges related to legal issues, data privacy, algorithm bias, and ethical considerations must be addressed to ensure equitable access and improved outcomes for all individuals.

摘要

随着人工智能(AI)的出现,出现了变革医疗服务和改善人群健康的新机遇。本综述提供了人工智能技术最新进展及其在人群层面改善心血管健康方面应用的最新概述。从预测分析到个性化干预,人工智能驱动的方法越来越多地被用于分析大量医疗数据、发现疾病模式以及优化资源分配。此外,可穿戴设备和远程监测系统等人工智能技术有助于持续心脏监测、疾病早期检测,并有望实现更及时的干预。此外,人工智能驱动的系统有助于医疗专业人员进行临床决策,从而提高准确性和治疗效果。通过使用人工智能系统增强现有数据源,如登记处和生物样本库,可以解决全新的研究问题,以识别新的机制和药物靶点。尽管人工智能在改善人群健康方面具有巨大潜力,但必须解决与法律问题、数据隐私、算法偏差和伦理考量相关的挑战,以确保所有人都能公平获得并改善健康结果。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/594e/12093147/ea3e60b6a4ae/ehaf125f1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/594e/12093147/cc9c12ccb2c8/ehaf125_ga.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/594e/12093147/ea3e60b6a4ae/ehaf125f1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/594e/12093147/cc9c12ccb2c8/ehaf125_ga.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/594e/12093147/ea3e60b6a4ae/ehaf125f1.jpg

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