Application of Artificial Intelligence in Hypertension Diagnosis: A Systematic Review

Abstract

High blood pressure (BP) is a major health concern that can lead to various cardiovascular diseases, serious complications, and even death. Although much progress has been made in the diagnosis and treatment of high BP, awareness of this medical condition and its effective control are not fully achieved. Nonetheless, artificial intelligence (AI) has created new opportunities for better detection and management of high BP. Therefore, this review investigated AI-related studies (2015-2025) performed for BP diagnosis. Overall, 48 studies using various AI methods (e.g., machine learning and deep learning) and covering different AI applications (i.e., non-invasive BP monitoring, early detection and classification of different types of high BP, and even disease risk prediction) were reviewed. Most AI models had very good accuracy (71–97%), and some even outperformed human experts. However, there were still problems, such as small sample sizes, lack of external validation, high data variability, and difficulties in understanding and interpreting complex models. Our findings revealed that AI can diagnose high BP more accurately, help people receive treatment more quickly, and even personalize their care. Nevertheless, some issues should be figured out before using AI. Researchers need to understand how these AI models act in actual hospitals and clinics, how they make their decisions, and how easily they can be integrated into the systems that doctors and nurses currently use. Otherwise, it is difficult for individuals to really trust this technology.

Keywords: Artificial intelligence, Hypertension, Diagnosis