BHF Glasgow Cardiovascular Research Centre, Institute of Cardiovascular and Medical Sciences, University of Glasgow.
Circ Res. 2021 Apr 2;128(7):1100-1118. doi: 10.1161/CIRCRESAHA.121.318106. Epub 2021 Apr 1.
Hypertension remains the largest modifiable cause of mortality worldwide despite the availability of effective medications and sustained research efforts over the past 100 years. Hypertension requires transformative solutions that can help reduce the global burden of the disease. Artificial intelligence and machine learning, which have made a substantial impact on our everyday lives over the last decade may be the route to this transformation. However, artificial intelligence in health care is still in its nascent stages and realizing its potential requires numerous challenges to be overcome. In this review, we provide a clinician-centric perspective on artificial intelligence and machine learning as applied to medicine and hypertension. We focus on the main roadblocks impeding implementation of this technology in clinical care and describe efforts driving potential solutions. At the juncture, there is a critical requirement for clinical and scientific expertise to work in tandem with algorithmic innovation followed by rigorous validation and scrutiny to realize the promise of artificial intelligence-enabled health care for hypertension and other chronic diseases.
尽管过去 100 年来已有有效的药物和持续的研究努力，高血压仍然是全球可改变的最大死因。高血压需要变革性的解决方案，以帮助减轻全球疾病负担。在过去十年中，人工智能和机器学习对我们的日常生活产生了重大影响，它们可能是实现这种转变的途径。然而，医疗保健中的人工智能仍处于起步阶段，要实现其潜力，需要克服许多挑战。在这篇综述中，我们从临床医生的角度介绍了人工智能和机器学习在医学和高血压中的应用。我们重点介绍了阻碍该技术在临床护理中实施的主要障碍，并描述了推动潜在解决方案的努力。目前，迫切需要临床和科学专业知识与算法创新相结合，然后进行严格的验证和审查，以实现人工智能在高血压和其他慢性病方面的医疗保健的承诺。
