Department of Internal Medicine, Icahn School of Medicine at Mount Sinai, Tenth Avenue, Suite 3A-09, New York, NY, 10019, USA.
Division of Nephrology, College of Physicians and Surgeons, Columbia University, New York, NY, USA.
Curr Hypertens Rep. 2018 Jul 6;20(9):75. doi: 10.1007/s11906-018-0875-x.
Evidence that artificial intelligence (AI) is useful for predicting risk factors for hypertension and its management is emerging. However, we are far from harnessing the innovative AI tools to predict these risk factors for hypertension and applying them to personalized management. This review summarizes recent advances in the computer science and medical field, illustrating the innovative AI approach for potential prediction of early stages of hypertension. Additionally, we review ongoing research and future implications of AI in hypertension management and clinical trials, with an eye towards personalized medicine.
Although recent studies demonstrate that AI in hypertension research is feasible and possibly useful, AI-informed care has yet to transform blood pressure (BP) control. This is due, in part, to lack of data on AI's consistency, accuracy, and reliability in the BP sphere. However, many factors contribute to poorly controlled BP, including biological, environmental, and lifestyle issues. AI allows insight into extrapolating data analytics to inform prescribers and patients about specific factors that may impact their BP control. To date, AI has been mainly used to investigate risk factors for hypertension, but has not yet been utilized for hypertension management due to the limitations of study design and of physician's engagement in computer science literature. The future of AI with more robust architecture using multi-omics approaches and wearable technology will likely be an important tool allowing to incorporate biological, lifestyle, and environmental factors into decision-making of appropriate drug use for BP control.
人工智能 (AI) 在预测高血压的危险因素及其管理方面的作用的证据正在出现。然而，我们远未利用创新的 AI 工具来预测这些高血压的危险因素，并将其应用于个性化管理。这篇综述总结了计算机科学和医学领域的最新进展，说明了用于预测高血压早期阶段的创新 AI 方法。此外，我们还回顾了人工智能在高血压管理和临床试验中的当前研究和未来意义，着眼于个性化医学。
尽管最近的研究表明 AI 在高血压研究中是可行且可能有用的，但 AI 驱动的护理尚未改变血压 (BP) 的控制。部分原因是缺乏关于 AI 在 BP 领域的一致性、准确性和可靠性的数据。然而，许多因素导致 BP 控制不佳，包括生物、环境和生活方式问题。AI 可以深入了解数据分析，告知开处方者和患者可能影响他们的 BP 控制的具体因素。迄今为止，人工智能主要用于研究高血压的危险因素，但由于研究设计和医生对计算机科学文献的参与存在局限性，尚未用于高血压管理。使用多组学方法和可穿戴技术构建更强大架构的 AI 的未来，可能成为将生物、生活方式和环境因素纳入适当药物使用决策以控制 BP 的重要工具。
