Seven machine learning models were developed and evaluated in terms of discrimination, calibration, and clinical utility. The SHAP (Shapley Additive Explanations) method was used to interpret the ...

Osteoporotic fragility fractures often lead to hospitalization and impose a significant economic burden. To investigate the clinical characteristics of hospitalized major osteoporotic fractures in ...

Abstract: Explainable Machine Learning (ML) models are an essential component of Clinical Decision Support Systems (CDSS), since they provide the transparency and interpretability that are essential ...

A practical review of explainable AI examines how transparency and interpretability improve trust in high-stakes ...

DataRobot AI Governance: Enterprise platform supporting explainable predictions, regulatory compliance, model documentation, and responsible AI lifecycle management. H2O AI Cloud: Artificial ...

The model building process made use of a number of fundamental libraries, namely, xgboost for gradient boosting machine learning algorithms, randomForest for ensemble tree learning methods, pso for ...

The actuarial methodology powering insurance risk models is advancing faster than most carriers realize. Here is what is ...

QuadSci, the most predictive and prescriptive AI for customer intelligence, has been selected as the winner of the 2026 Machine Learning Company of the Year award in the 9th annual AI Breakthrough ...

Abstract: The concept of a decentralized smart grid has emerged as a viable approach for efficiently managing and distributing electrical energy. Ensuring the stability and reliability of the grid, ...

A privacy-preserving marketing framework applies homomorphic encryption to perform machine learning on encrypted ...