Fuzzy regression models extend traditional statistical regression by integrating fuzzy set theory to better handle imprecision and uncertainty inherent in many real-world data sets. These models ...

Innovative machine learning models using routine clinical data offer superior stroke risk prediction in atrial fibrillation, ...

What was the rationale behind applying machine learning (ML) models to improve identification probability in the absence of ...

Built on a new architecture KumoRFM-2 achieves state-of-the-art results across 41 predictive tasks and four major benchmarks, ...

Forecasting inflation has become a major challenge for central banks since 2020, due to supply chain disruptions and economic uncertainty post-pandemic. Machine learning models can improve forecasting ...

Young, T. , Guymon, J. , Pankow, M. and Ngaile, G. (2026) A Material Removal Prediction Framework for Ball EEM Polishing in ...

The increasing global demand for sustainable energy and carbon materials, alongside pressing environmental concerns, ...

A machine-learning model trained on fewer than 300 molecules has flagged diatomic pairs with record-high electric dipole moments, several of them in combinations that chemists had not seriously ...