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Machine Learning and Artificial Intelligence for Research on Hypertension

Fatima Zohra Khamissi1, Lorelle Sun1, Paige Johnson1

  • 1Cardiovascular Center, Medical College of Wisconsin, Milwaukee, WI, USA.

American Journal of Hypertension
|April 19, 2025
PubMed

Insights

Hypertension, a major global health risk, affects 1.28 billion adults, with many unaware of their condition. Emerging artificial intelligence (AI) and machine learning (ML) technologies offer new avenues for improving hypertension detection and management worldwide.

Area of Science:

  • Cardiovascular Medicine
  • Public Health
  • Medical Informatics

Background:

  • Hypertension is the leading modifiable risk factor for global mortality and cardiovascular disease.
  • An estimated 1.28 billion adults worldwide have hypertension, but nearly half are undiagnosed or undertreated.
  • Effective hypertension management is critical for reducing morbidity and mortality.

Purpose of the Study:

  • To highlight the global burden of hypertension and the need for improved management strategies.
  • To discuss the evolving role of artificial intelligence (AI) and machine learning (ML) in hypertension care.
  • To emphasize the importance of early detection, lifestyle changes, and pharmacological treatments.

Main Methods:

  • Review of global hypertension statistics and current clinical guidelines.
  • Discussion of the impact of AI and ML on hypertension research and patient outcomes.
  • Analysis of hypertension definition and target blood pressure (BP) recommendations.

Main Results:

  • Hypertension affects a significant portion of the global adult population.
  • A substantial number of individuals with hypertension remain undiagnosed or inadequately managed.
  • AI and ML are emerging as transformative tools in the field of hypertension.

Conclusions:

  • Early detection and comprehensive management are essential for mitigating hypertension-related health risks.
  • AI and ML hold significant promise for advancing hypertension care and improving global health outcomes.
  • Continued research and implementation of innovative technologies are crucial for addressing the hypertension epidemic.

Keywords:
Blood pressureartificial intelligencehypertensionmachine learning

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