Tag: SHAP

Researchers combined Bayesian optimization, machine learning and explainable AI to identify silver-cobalt bimetallic nanoparticles that reduce nearly all p-nitrophenol in ...

Researchers in Türkiye used a hybrid stacking ensemble model and real distribution grid data to forecast hourly electric vehicle charging ...

An interpretable machine-learning study quantifies how iron loading in biochar improves heavy-metal removal while steadily eroding CO₂ capture capacity, mapping ...

A large MIMIC-IV analysis found that elevated serum osmolality was independently associated with inflammatory bowel disease in hospitalized patients with ...

Researchers in China built an interpretable Random Forest model that predicts which women with diminished ovarian reserve will progress to ...

A study of 1,008 patients in Tianjin identifies three distinct craving profiles in adolescent-onset new psychoactive substance use disorder and ...

An interpretable machine-learning study of Shahu Lake shows that the drivers of algal blooms shift with the seasons, from long-term ...

Researchers have developed UbiQVision, a framework that fuses explainable AI attributions from deep learning ensembles using Dempster–Shafer evidence theory to ...

An interpretable machine learning model trained on 20 years of rural Spanish registry data outperforms logistic regression in predicting 30-day ...

A proof-of-concept study shows that differentially private, explainable AI can detect vasovagal syncope from tilt-test data with minimal accuracy loss, ...