Tag: SHAP

Researchers in China built a six-variable nomogram from national CHARLS survey data that uses logistic regression and SHAP analysis to ...

A new multimodal AI framework ranks classroom features by importance with 88.6 percent prediction accuracy, identifying linguistic coherence, student engagement, ...

A new study shows that an interpretable AI model fusing 18F-PSMA-1007 PET/CT and multiparametric MRI can predict prostate cancer aggressiveness ...

A machine learning analysis of 1,525 SEER records finds that concurrent chemoradiotherapy is associated with roughly 30 percent better disease-specific ...

Researchers have built an explainable ensemble deep learning framework that fuses four transfer learning models using CMAES optimization to classify ...

Interpretable machine learning at Shibaura Institute of Technology reveals that the effect of surface roughness on the pitting resistance of ...

A new BMC Public Health study presents a safety-first machine learning framework that segments Iranian adults into vaccine-hesitancy profiles and ...

Australian researchers used mid-infrared spectroscopy and explainable machine learning to accurately predict how much stable carbon soils hold and how ...

A new analysis of Bangladesh's 2022 Demographic and Health Survey combines logistic regression with machine learning to identify the demographic ...

An interpretable machine learning framework shows that high-dose organic fertilization, especially pig manure, improves blueberry fruit quality through rhizosphere pH ...