Application of artificial intelligence in hypertension.

Area of Science:

• Cardiology
• Medical Informatics
• Artificial Intelligence

Background:

• Hypertension is a major modifiable risk factor for cardiovascular disease, with increasing incidence globally due to aging and lifestyle changes.
• Low hypertension control rates are attributed to poor medication adherence, lack of awareness, and multifactorial influences (diet, lifestyle, genetics).
• Artificial intelligence (AI) presents a data-driven approach to understanding complex chronic diseases like hypertension.

Purpose of the Study:

• To provide a clinician-centered review of recent AI applications in hypertension.
• To assess the clinical relevance and understanding of AI-driven hypertension research.
• To explore AI's role in blood pressure measurement, diagnosis, prognosis, and management.

Main Methods:

• Systematic review of recent AI-based studies related to hypertension.
• Focus on studies with clinical relevance and clinician accessibility.
• Categorization of AI applications across different aspects of hypertension care.

Main Results:

• Existing AI studies in hypertension are often descriptive and lack clinical applicability.
• AI demonstrates potential in analyzing multifactorial data for hypertension.
• Further research is needed to translate AI findings into practical clinical tools.

Conclusions:

• AI holds significant promise for improving hypertension diagnosis and management.
• Clinician-centered AI research is crucial for effective implementation in patient care.
• Bridging the gap between AI research and clinical practice is essential for better hypertension control.