Machine Learning-Based Plasma Protein Risk Score Improves Atrial Fibrillation Prediction Over Clinical and Genomic Models
Circulation: Genomic and Precision Medicine
JUNE 17, 2025
Circulation: Genomic and Precision Medicine, Ahead of Print. BACKGROUND:Clinical factors discriminate incident atrial fibrillation (AF) risk with moderate accuracy, with only modest improvement after incorporation of polygenic risk scores. Whether emerging large-scale proteomic profiling can augment AF risk estimation is unknown.METHODS:In the UK Biobank cohort, we derived and validated a machine learning model to predict incident AF risk using serum proteins (Pro-AF).
Let's personalize your content