Hypertension is among the most important risk factors for cardiovascular disease, chronic kidney disease, and dementia. The artificial intelligence (AI) field is advancing quickly, and there has been little discussion on how AI could be leveraged for improving the diagnosis and management of hypertension. AI technologies, including machine learning tools, could alter the way we diagnose and manage hypertension, with potential impacts for improving individual and population health. The development of successful AI tools in public health and health care systems requires diverse types of expertise with collaborative relationships between clinicians, engineers, and data scientists. Unbiased data sources, management, and analyses remain a foundational challenge. From a diagnostic standpoint, machine learning tools may improve the measurement of blood pressure and be useful in the prediction of incident hypertension. To advance the management of hypertension, machine learning tools may be useful to find personalized treatments for patients using analytics to predict response to antihypertension medications and the risk for hypertension-related complications. However, there are real-world implementation challenges to using AI tools in hypertension. Herein, we summarize key findings from a diverse group of stakeholders who participated in a workshop held by the National Heart, Lung, and Blood Institute in March 2023. Workshop participants presented information on communication gaps between clinical medicine, data science, and engineering in health care; novel approaches to estimating BP, hypertension risk, and BP control; and real-world implementation challenges and issues.

中文翻译：

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人工智能时代的高血压诊断和管理转型：2023 年国家心肺血液研究所 （NHLBI） 研讨会报告。


高血压是心血管疾病、慢性肾病和痴呆最重要的危险因素之一。人工智能 （AI） 领域发展迅速，关于如何利用人工智能来改善高血压的诊断和管理的讨论很少。人工智能技术（包括机器学习工具）可能会改变我们诊断和管理高血压的方式，对改善个人和人群健康产生潜在影响。在公共卫生和医疗保健系统中开发成功的 AI 工具需要各种类型的专业知识，以及临床医生、工程师和数据科学家之间的合作关系。公正的数据源、管理和分析仍然是一个基本挑战。从诊断的角度来看，机器学习工具可以改善血压的测量，并有助于预测新发高血压。为了推进高血压的管理，机器学习工具可能有助于使用分析来预测对抗高血压药物的反应和高血压相关并发症的风险，从而为患者找到个性化的治疗方法。然而，在高血压中使用 AI 工具存在实际的实施挑战。在本文中，我们总结了参加美国国家心肺血液研究所于 2023 年 3 月举办的研讨会的不同利益相关者群体的主要发现。研讨会参与者介绍了有关医疗保健领域临床医学、数据科学和工程之间沟通差距的信息;估计血压、高血压风险和血压控制的新方法;以及现实世界的实施挑战和问题。