Key result
AI and wearables optimize hypertension diagnosis and treatment through machine learning and real-time health insights.
Why the study?
Hypertension presents a major global health challenge with traditional diagnosis and treatment relying on periodic monitoring and antihypertensive drugs, prompting investigation into smart technology and machine learning to optimize early detection and personalized management.
Integration of artificial intelligence and wearable technology provides a promising personalized approach for the early detection and optimized management of hypertension.
May support AI-enhanced hypertension monitoring; leaves open whether outcomes improve in prospective trials.
Hypertension, a widespread cardiovascular issue, presents a major global health challenge. Traditional diagnosis and treatment methods involve periodic blood pressure monitoring and prescribing antihypertensive drugs. Smart technology integration in healthcare offers promising results in optimizing the diagnosis and treatment of various conditions. We investigate its role in improving hypertension diagnosis and treatment effectiveness using machine learning algorithms for early and accurate detection. Intelligent models trained on diverse datasets (encompassing physiological parameters, lifestyle factors, and genetic information) to detect subtle hypertension risk patterns. Adaptive algorithms analyze patient-specific data, optimizing treatment plans based on medication responses and lifestyle habits. This personalized approach ensures effective, minimally invasive interventions tailored to each patient. Wearables and smart sensors provide real-time health insights for proactive treatment adjustments and early complication detection.
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Juyal et al. (2024) conducted a review in Hypertension. Artificial intelligence and modern wearables vs. Traditional diagnosis and treatment methods was evaluated. Artificial intelligence and modern wearables optimize hypertension diagnosis and treatment through machine learning algorithms for early detection and real-time health insights.
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