Why the study?
Hypertension disproportionately affects low- and middle-income countries, and this review aimed to identify current research, innovations, and developments in applying AI-based tools for hypertension prediction and risk assessment specifically in these settings.
Do artificial intelligence-based tools accurately predict and assess the risk of hypertension in low- and middle-income countries?
Population
5 studies on AI-based risk assessment and prediction of hypertension in LMICs
Design
Scoping review
Key result
Artificial intelligence applications for hypertension risk assessment and prediction in low- and middle-income countries achieved prediction accuracies ranging from 78% to 97%.
Authors
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AI tools may aid hypertension screening in LMICs; leaves open need for prospective validation before clinical adoption.
Do artificial intelligence-based tools accurately predict and assess the risk of hypertension in low- and middle-income countries?
AI-based tools demonstrate high accuracy (78-97%) for hypertension risk prediction in LMICs, highlighting their potential to enhance disease prevention and management in resource-limited settings.
Sasu et al. (2026) conducted a review in Hypertension (n=5). Artificial intelligence (AI) algorithms was evaluated on Prediction accuracy of AI models. Artificial intelligence applications for hypertension risk assessment and prediction in low- and middle-income countries achieved prediction accuracies ranging from 78% to 97%.