Artificial Intelligence in Hypertension Management: Promise Must Precede Practice

Hypertension remains one of the most important modifiable risk factors for cardiovascular disease worldwide, yet blood pressure control rates remain suboptimal despite advances in diagnosis and treatment. Artificial intelligence (AI) has emerged as a promising tool to improve hypertension care through enhanced risk prediction, continuous monitoring, and clinical decision support. Enthusiasm surrounding AI must be balanced against challenges related to algorithmic bias, model interpretability, data quality, and clinical implementation. While AI has the potential to transform hypertension management, its greatest challenge is no longer predictive accuracy but successful integration into real-world clinical practice. This editorial discusses the opportunities and limitations of AI in hypertension care and argues that implementation science, transparency, and equitable deployment should become the next priorities for the field.

Authors

Publication Details

Journal
Cureus
Published
2026-06-18
DOI
https://doi.org/10.7759/cureus.111109
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
0.00
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article

Artificial Intelligence in Hypertension Management: Promise Must Precede Practice

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Cureus
Artificial Intelligence in Healthcare and Education
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Artificial Intelligence in Hypertension Management: Promise Must Precede Practice

Sarwan Kumar, Kunj Rajeshbhai Ghantiwala, Ruchik Kevadiya, Arpit R Thakor, Pradeep Pentapurthy
article en

Abstract

Hypertension remains one of the most important modifiable risk factors for cardiovascular disease worldwide, yet blood pressure control rates remain suboptimal despite advances in diagnosis and treatment. Artificial intelligence (AI) has emerged as a promising tool to improve hypertension care through enhanced risk prediction, continuous monitoring, and clinical decision support. Enthusiasm surrounding AI must be balanced against challenges related to algorithmic bias, model interpretability, data quality, and clinical implementation. While AI has the potential to transform hypertension management, its greatest challenge is no longer predictive accuracy but successful integration into real-world clinical practice. This editorial discusses the opportunities and limitations of AI in hypertension care and argues that implementation science, transparency, and equitable deployment should become the next priorities for the field.

Cureus
Openalex Percentile: Top 9%
Artificial Intelligence in Healthcare and Education
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