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Controversy in Hypertension: Pro-Side of the Argument Using Artificial Intelligence for Hypertension Diagnosis and
Antonis A Armoundas1, Faraz S Ahmad2, Zachi I Attia3
1Cardiovascular Research Center, Massachusetts General Hospital and Broad Institute, Massachusetts Institute of Technology, Boston (A.A.A.).
Insights
Artificial intelligence (AI) offers potential for personalized hypertension management by integrating diverse data. However, widespread clinical adoption of AI in hypertension care is currently limited, requiring further evidence generation for equitable implementation.
Area of Science:
- Cardiovascular Medicine
- Medical Informatics
- Public Health
Background:
- Hypertension is a major public health challenge due to its high prevalence and links to cardiovascular diseases.
- Low awareness and suboptimal diagnosis hinder effective hypertension management.
- Artificial intelligence (AI) enables integrative analysis of large, diverse datasets for hypertension.
Purpose of the Study:
- To examine the current state of AI in hypertension management from a clinician's perspective.
- To identify challenges and opportunities for AI adoption in precision hypertension care.
- To propose recommendations for equitable, large-scale implementation of AI in hypertension.
Main Methods:
- Review of current AI applications in hypertension diagnosis, treatment, and management.
- Analysis of data integration from omics, clinical, wearable, social, behavioral, and environmental sources.
- Clinician-centric perspective on AI's potential and limitations in hypertension care.
Main Results:
- AI holds transformative potential for data-driven, personalized hypertension diagnosis and management.
- Significant gaps exist in the clinical adoption and evidence base for AI in hypertension.
- Current AI advancements focus on discovery and drug development, with limited large-scale patient care integration.
Conclusions:
- Equitable precision hypertension care requires addressing barriers to AI clinical implementation.
- Evidence generation is crucial for the widespread adoption of AI-based hypertension solutions.
- A clinician-centric approach is vital for advancing AI in managing hypertension effectively.
Abstract:
Hypertension presents the largest modifiable public health challenge due to its high prevalence, its intimate relationship to cardiovascular diseases, and its complex pathogenesis and pathophysiology. Low awareness of blood pressure elevation and suboptimal hypertension diagnosis serve as the major hurdles in effective hypertension management. Advances in artificial intelligence in hypertension have permitted the integrative analysis of large data sets including omics, clinical (with novel sensor and wearable technologies), health-related, social, behavioral, and environmental sources, and hold transformative potential in achieving large-scale, data-driven approaches toward personalized diagnosis, treatment, and long-term management. However, although the emerging artificial intelligence science may advance the concept of precision hypertension in discovery, drug targeting and development, patient care, and management, its clinical adoption at scale today is lacking. Recognizing that clinical implementation of artificial intelligence-based solutions need evidence generation, this opinion statement examines a clinician-centric perspective of the state-of-art in using artificial intelligence in the management of hypertension and puts forward recommendations toward equitable precision hypertension care.
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