Artificial Intelligence and Hypertension: Recent Advances and Future Outlook

Area of Science:

• Cardiovascular Medicine
• Medical Informatics
• Artificial Intelligence

Background:

• Hypertension (HTN) presents a significant global public health challenge.
• Artificial intelligence (AI) is emerging as a powerful tool for addressing HTN.
• AI facilitates precision medicine in cardiovascular (CV) diseases.

Purpose of the Study:

• To explore the potential of AI in the prevention and treatment of hypertension.
• To highlight AI's capability in handling multimodal and big data for HTN research.
• To discuss the transformative impact of AI-integrated HTN care on clinical practice.

Main Methods:

• AI algorithms analyze diverse datasets including genetics, epigenetics, proteomics, metabolomics, CV imaging, socioeconomic, behavioral, and environmental factors.
• AI identifies HTN risk factors, phenotypes, and predicts incident HTN.
• AI aids in diagnosing HTN, estimating blood pressure (BP), and developing novel BP measurement methods.

Main Results:

• AI can identify risk factors and phenotypes of HTN.
• AI demonstrates potential in predicting HTN risk and diagnosing the condition.
• AI aids in optimizing treatment adherence and success, and analyzing factors associated with CV outcomes.

Conclusions:

• AI-integrated hypertension care promises personalized prevention and treatment strategies.
• AI can determine optimal patient-specific BP goals and effective medication regimens.
• While AI's role in HTN is growing, further studies are essential to demonstrate its full applicability.