Results 151 to 160 of about 25,341,143 (317)

An interpretable nomogram with SHAP analysis predicts thrombotic failure of forearm arteriovenous fistulas. [PDF]

Front Surg
Xu Y, Jiang L, Zhang H, Ni R, Qian P, Wang Z, Li W.   +6 more
europepmc   +1 more source

Research on a Predictive Model for Microalbuminuria in Type 2 Diabetes Based on Machine Learning and SHAP Analysis. [PDF]

Int J Endocrinol
Liu Z, Zhou Z, Sun Y, Du X, Zhang H, Ji C.   +5 more
europepmc   +1 more source

Gene Expression-Based Colorectal Cancer Prediction Using Machine Learning and SHAP Analysis. [PDF]

Genes (Basel)
Yin Y, Yang Z, Li X, Gong S, Xu C.
europepmc   +1 more source

An XGBoost-SHAP analysis of the driving factors of carbon emissions in China's first-tier cities. [PDF]

Sci Rep
Li Y, He Y, Yang F, An H, Li J, Xie Y.
europepmc   +1 more source

Machine translationese of large language models: Dependency triplets, text classification, and SHAP analysis. [PDF]

PLoS One
Zhang S, Zhao C.
europepmc   +1 more source

Accurate and interpretable prediction of chemical oxygen demand using explainable boosting algorithms with SHAP analysis. [PDF]

Sci Rep
Merabet K, Kim S, Heddam S, Di Nunno F, Granata F, Kisi O, Adnan RM, Zounemat-Kermani M, Külls C.   +8 more
europepmc   +1 more source

Prediction of Properties of Polymer Composite Formulations Using Ensemble Models With Feature Generation

Journal of Applied Polymer Science, EarlyView.
This study develops an interpretable machine‐learning framework to predict multiple properties of polymer composites based on composition and processing variables. By combining ensemble models with composition‐based feature generation and SHAP‐based interpretation, the approach reveals composition‐property relationships and supports efficient multi ...
Dong Ryeol Shin, Sung Kwang Lee
wiley   +1 more source

Exploring the Impact of Physical Activity Metrics on Calorie Consumption: A Machine Learning Approach Combined with SHAP Analysis. [PDF]

Sci Rep
Lin S, Zhang Y.
europepmc   +1 more source

Identifying Systemic Lupus Erythematosus From Serum Proteomic Profiles Using Machine Learning and Genetic Risk Stratification

Arthritis &Rheumatology, EarlyView.
Objective Proteome‐wide risk models for lupus remain underexplored. We developed classification models to identify lupus from serum proteomic profiles. Methods Patients with lupus and individuals with other autoimmune diseases in the UK Biobank were included.
Mehmet Hocaoǧlu, Jishnu Das, Amr H. Sawalha   +2 more
wiley   +1 more source

Interpretable Taxi-Out Time Prediction of Departure Flights Using Stacking Ensemble Learning and SHAP Analysis. [PDF]

Sci Rep
Wu T, Mao Y, Huang J, Zeng X, Ma J, Jia X.   +5 more
europepmc   +1 more source