Machine Learning and Artificial Intelligence for Research on Hypertension
Hypertension continues to be the leading modifiable risk factor for mortality globally, contributing significantly to cardiovascular disease. The American Heart Association (AHA) 2017 Hypertension Guidelines define hypertension as blood pressure (BP) ≥ 130/80 mmHg and recommend a target BP of <130-140/80 mmHg for most adults. Effective management of hypertension is crucial in reducing morbidity and mortality, and current clinical guidelines emphasize the importance of early detection, lifestyle modifications, and pharmacological treatment to mitigate long-term health risks. With the recent development and advancement of artificial intelligence (AI) and machine learning (ML), the landscape for hypertension care and research is evolving at an accelerating pace to improve health outcomes worldwide.
Authors
- Ivor J. Benjamin (ORCID: https://orcid.org/0000-0003-3310-3957)
- Fatima Zohra Khamissi (ORCID: https://orcid.org/0000-0002-1652-607X)
- Sarah Shah (ORCID: https://orcid.org/0000-0003-1055-6064)
- Lorelle Sun
- Paige Johnson
Institutions
- Medical College of Wisconsin (US)
- University of Oxford (GB)
- Science Oxford (GB)
Publication Details
- Journal
- American Journal of Hypertension
- Published
- 2025-03-30
- DOI
- https://doi.org/10.1093/ajh/hpaf051
- Citations
- 1
- Primary Topic
- Blood Pressure and Hypertension Studies
- Type
- article
- Field-Weighted Citation Impact
- 1.39