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用于心血管临床试验设计与实施的人工智能和数字工具。

Artificial intelligence and digital tools for design and execution of cardiovascular clinical trials.

作者信息

Hu Jiun-Ruey, Power John R, Zannad Faiez, Lam Carolyn S P

机构信息

Section of Cardiovascular Medicine, School of Medicine, Yale University, New Haven, CT, USA.

Department of Cardiology, Smidt Heart Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA.

出版信息

Eur Heart J. 2025 Mar 3;46(9):814-826. doi: 10.1093/eurheartj/ehae794.

Abstract

Recent advances have given rise to a spectrum of digital health technologies that have the potential to revolutionize the design and conduct of cardiovascular clinical trials. Advances in domain tasks such as automated diagnosis and classification, synthesis of high-volume data and latent data from adjacent modalities, patient discovery, telemedicine, remote monitoring, augmented reality, and in silico modelling have the potential to enhance the efficiency, accuracy, and cost-effectiveness of cardiovascular clinical trials. However, early experience with these tools has also exposed important issues, including regulatory barriers, clinical validation and acceptance, technological literacy, integration with care models, and health equity concerns. This narrative review summarizes the landscape of digital tools at each stage of clinical trial planning and execution and outlines roadblocks and opportunities for successful implementation of digital tools in cardiovascular clinical trials.

摘要

最近的进展催生了一系列数字健康技术,这些技术有可能彻底改变心血管临床试验的设计和实施。在诸如自动诊断和分类、大量数据和来自相邻模式的潜在数据的合成、患者发现、远程医疗、远程监测、增强现实以及计算机模拟等领域任务方面的进展,有可能提高心血管临床试验的效率、准确性和成本效益。然而,这些工具的早期使用也暴露了一些重要问题,包括监管障碍、临床验证和接受度、技术素养、与护理模式的整合以及对健康公平性的担忧。这篇叙述性综述总结了临床试验规划和执行各阶段数字工具的情况,并概述了在心血管临床试验中成功实施数字工具的障碍和机遇。

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