Predictive performance of the xgboost model for health status outcomes.

<p>Predictive performance of the xgboost model for health status outcomes.</p>

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التفاصيل البيبلوغرافية
المؤلف الرئيسي:	Ju Youn Jung (22139209) (author)
مؤلفون آخرون:	Young Ho Yun (7507208) (author)
منشور في:	2025
الموضوعات:	Biotechnology Cancer Science Policy Environmental Sciences not elsewhere classified Biological Sciences not elsewhere classified Mathematical Sciences not elsewhere classified Information Systems not elsewhere classified xlink "> despite validate predictive models shapley additive explanation repeated stratified k important features identified final dataset consisted established prediction models creating dependence plots also providing interpretations 42 predictive features specific health outcomes prospective cohort study extreme gradient boost 256 cancer survivors existing prediction model including decision trees overall health status health status separately secondary health statuses xai technique known interpret individual outcomes xgboost predictive model health status health statuses xgboost model survived cancer study represents gradient boosting model comparison appropriate model xgboost ), including physical spiritual well shap ). results using random forest primary objectives management strategies leveraged shap first endeavor critical effects based survey among individuals
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