Hypertension, a leading cause of cardiovascular disease and premature death, remains incompletely understood despite extensive research. Indeed, even though numerous drugs are available, achieving adequate blood pressure control remains a challenge, prompting recent interest in artificial intelligence. To promote the use of machine learning in cardiovascular medicine, this review provides a brief introduction to machine learning and reviews its notable applications in hypertension management and research, such as disease diagnosis and prognosis, treatment decisions, and omics data analysis. The challenges and limitations associated with data-driven predictive techniques are also discussed. The goal of this review is to raise awareness and encourage the hypertension research community to consider machine learning as a key component in developing innovative diagnostic and therapeutic tools for hypertension. By integrating traditional cardiovascular risk factors with genomics, socioeconomic, behavioral, and environmental factors, machine learning may aid in the development of precise risk prediction models and personalized treatment approaches for patients with hypertension.

中文翻译：

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人工智能、机器学习和 ChatGPT 在高血压领域的应用

尽管进行了广泛的研究，但高血压是心血管疾病和过早死亡的主要原因，但人们仍未完全了解它。事实上，尽管有多种药物可用，但实现充分的血压控制仍然是一个挑战，这引发了人们对人工智能的兴趣。为了促进机器学习在心血管医学中的应用，本文简要介绍了机器学习，并回顾了其在高血压管理和研究中的显着应用，例如疾病诊断和预后、治疗决策和组学数据分析。还讨论了与数据驱动的预测技术相关的挑战和局限性。本次综述的目的是提高认识并鼓励高血压研究界将机器学习视为开发创新的高血压诊断和治疗工具的关键组成部分。通过将传统的心血管危险因素与基因组学、社会经济、行为和环境因素相结合，机器学习可能有助于为高血压患者开发精确的风险预测模型和个性化治疗方法。