Tag: SHAP

Researchers in Qingdao developed an interpretable XGBoost model that distinguishes gastric cancer from intestinal metaplasia in patients with psychological symptoms ...

Chinese researchers built an interpretable CatBoost-based machine learning model that predicts three-year overall survival in Waldenström Macroglobulinemia patients with an ...

A study of 144 sites in Zhijin County, southwestern China, combines kriging, Geodetector, and explainable machine learning to map soil ...

Researchers in China built a LightGBM-based prediction model that identifies which patients with proliferative diabetic retinopathy are likely to have ...

A new EEG study finds that children with autism show reduced frontal beta activity, heightened temporo-occipital delta activity, and lower ...

A new federated learning framework lets hospitals train chest X-ray diagnostic AI collaboratively without sharing patient data, and it outperforms ...

A sweeping new survey of 57 studies finds that machine learning and deep learning models report accuracy as high as ...

A multicenter study of 150 children with achondroplasia shows that an explainable stacked ensemble model outperformed classical penalized statistical methods ...

A rigorous evaluation of 126 machine learning pipelines on data from more than 3,000 Golden Retrievers shows that routine laboratory ...

Researchers fused morphometric basin analysis with machine learning to map flood susceptibility across four Bayelsa State catchments, revealing hidden high-risk ...