A Bayesian-optimized Gaussian process regression framework accurately predicts the splitting tensile strength of concrete containing supplementary cementitious materials using eight ...
A multi-method explainable artificial intelligence study reveals how hybrid forecasting models rely on short-term residual dynamics to predict data center ...
A retrospective analysis of 1,101 serum samples used explainable artificial intelligence to prioritize circulating microRNAs that distinguished pancreatic cancer from ...
Researchers in Iran trained an optimized gradient boosting model on 419 tested deep beams and used SHAP analysis to make ...
Researchers in Turkey have built a leakage-aware, explainable AI framework that predicts quality risk in textile manufacturing, converts model explanations ...
Researchers in China have built an explainable AI framework that predicts student readiness for Industry 4.0 careers with 98.92 percent ...
Researchers used explainable machine learning to predict and interpret the compressive strength of sustainable SCM-based concrete, finding LightGBM the most ...
Researchers in Türkiye used an explainable machine learning framework combining XGBoost and SHAP to identify age and postpartum diseases as ...
Researchers at Fayoum University show that a simple averaged ensemble of machine learning models, evaluated on the OhioT1DM dataset with ...
Researchers at the University of Catania have built a modular computational framework that ranks RNA-lipid nanoparticle formulations for safety and ...
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