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Interpretable Lifestyle-Based Machine Learning Models for Ten-Year Cardiovascular Risk Prediction using data from the UK Biobank
2026-02-01
health informatics
Title + abstract only
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BackgroundCardiovascular diseases (CVDs) remain the leading global cause of morbidity and mortality. In clinical practice, 10-year risk prediction tools such as the Pooled Cohort Equations, QRISK3, and SCORE2 are widely used because of their transparency and clinical trustworthiness, but they rely heavily on biomarkers and medical history. Hence, most recommendations concentrate on pharmaceutical or procedural management, and in many situations, crucial biomarker indicators are unavailable, maki...
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