Researchmlvenous thromboembolismgene expressionmicroarray
Machine Learning Predicts VTE From Blood Genes
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7.4
Researchers report in JMIR Medical Informatics (2026) a VTE prediction study using whole-blood gene expression and 20 machine-learning algorithms. They trained models on GSE19151 (70 VTE, 63 controls) and validated on GSE48000 (107 VTE, 25 controls); nine algorithms achieved external AUCs above 0.75 while k-nearest neighbor underperformed. The authors suggest combining these models with D-dimer testing could enhance VTE diagnostic accuracy.
Scoring Rationale
Solid external validation and journal publication drive score, but moderate novelty and limited cohort sizes constrain impact.
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