The predictive performance on test set.

<div><p> Background </p><p>Venous thromboembolism (VTE) is a life-threatening complication commonly occurring after acute ischemic stroke (AIS), with an increased risk of mortality. Traditional risk assessment tools lack precision in predicting VTE in AIS patients due to the...

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Bibliographic Details
Main Author:	Youli Jiang (15249070) (author)
Other Authors:	Ao Li (15375) (author), Zhihuan Li (10233018) (author), Yanfeng Li (113424) (author), Rong Li (72042) (author), Qingshi Zhao (266307) (author), Guisu Li (20896561) (author)
Published:	2025
Subjects:	Neuroscience Biotechnology Developmental Biology Cancer Mathematical Sciences not elsewhere classified Information Systems not elsewhere classified shapley additive explanations leveraging machine learning large vessel occlusion positive predictive value negative predictive value highest predictive accuracy evaluated using area enhance model interpretability xlink "> among shap analysis revealed interpretable risk prediction gbm model achieved acute ischemic stroke predict vte risk auc ), sensitivity ais patients due xlink "> gbm model risk patients model performance interpretable method increased risk ais using rf ), predictive models ppv ), ais ), venous thromboembolism study provides reducing morbidity random forest premorbid mrs predicting vte lr ). logistic regression key predictors identifying high dimer levels december 2023 december 2021 83 %)
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The predictive performance on test set.

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