Researchers from Peking University have conducted a comprehensive systematic review on the integration of machine learning into statistical methods for disease risk prediction models, shedding light ...

Dr. James McCaffrey of Microsoft Research presents a full-code, step-by-step tutorial on this powerful machine learning technique used to predict a single numeric value. A regression problem is one ...

Dr. James McCaffrey presents a complete end-to-end demonstration of linear regression with two-way interactions between ...

Logistic regression is the most cost-effective model for medial vascular calcification classification, with a mean ICER of $278 using five low-cost features. Despite similar diagnostic accuracy, ...

A hybrid fuzzy neural network model enhances prediction accuracy of hardness properties in high-performance concrete, ...

Mînzu, V. and Arama, I. (2025) A New Method to Predict the Mechanical Behavior for a Family of Composite Materials. Journal ...

A recent study has developed a highly accurate risk prediction framework for preterm birth (PTB) that could broaden the potential of AI-driven multi-omics applications in precision obstetrics and ...

The existing prediction models for severe complications of preeclampsia are most accurate only in the two days after hospital ...