人工智能方法——心血管远程医疗的前景?]

IF 0.7
Deutsche medizinische Wochenschrift (1946) Pub Date : 2025-09-01 Epub Date: 2025-09-09 DOI:10.1055/a-2593-7851
Meike Hiddemann, Kerstin Köhler, Wilhelm Haverkamp, Juliane Köhler, Maximilian Bauser, Friedrich Köhler
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引用次数: 0

摘要

根据联邦联合委员会(G-BA)的决定,自2022年以来,德国估计有15万至20万心力衰竭(HF)患者符合心衰远程监测的纳入标准。目前,只有少数人工智能(AI)应用程序用于标准的心血管远程医疗护理。然而,人工智能应用可以通过识别多个数据源中的模式来提高现有远程医疗传感器技术的预测准确性。基于人工智能的生物标志物也正在开发中,用于远程医疗传感器技术。语音分析识别肺充血似乎是一个很有前途的方法。在未来,基于人工智能的决策支持系统可以帮助优化远程医疗中心的诊断过程。大型语言模型提供了支持诊断过程的潜力。欧盟的人工智能法规已经建立了第一个框架,用于测试医疗保健领域基于人工智能的新技术。现实世界的实验室提供了在受保护的环境中研究创新技术的机会。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
[Artificial Intelligence Methods - a Perspective for Cardiovascular Telemedicine?]

Since 2022, an estimated 150000 to 200000 patients with heart failure (HF) in Germany have met the inclusion criteria for HF telemonitoring in accordance with the Federal Joint Committee's (G-BA) decision. Currently, only a few artificial intelligence (AI) applications are used in standard cardiovascular telemedicine care. However, AI applications could improve the predictive accuracy of existing telemedical sensor technology by recognising patterns across multiple data sources. AI-based biomarkers are also being developed for use in telemedical sensor technology. Voice analysis to recognise pulmonary congestion appears to be a promising approach. In the future, AI-based decision support systems could help optimise the diagnostic process in telemedicine centres. Large language models offer the potential to support the diagnostic process. The European Union's AI regulation has established the first framework for testing new AI-based technologies in healthcare. Real-world laboratories provide an opportunity to research innovative technologies in a protected environment.

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