In food drying applications, machine learning has demonstrated strong capability in predicting drying rates, moisture ...

With climate change posing an unprecedented global challenge, the demand for environmentally friendly solvents in green ...

Recent developments in machine learning techniques have been supported by the continuous increase in availability of high-performance computational resources and data. While large volumes of data are ...

A research team demonstrates that hyperspectral sensing, combined with advanced artificial intelligence, can accurately estimate multiple biochemical and mineral traits in grapevine leaves at once.

Researchers at National University of Singapore used multiple interpretable machine learning methods to predict traffic congestion in in Alameda ...

Introduction Application of artificial intelligence (AI) tools in the healthcare setting gains importance especially in the domain of disease diagnosis. Numerous studies have tried to explore AI in ...

Explainable AI plays a central role in validating model behavior. Using established explainability techniques, the study examines which financial variables drive fraud predictions. The results show a ...

The GC–MS dataset was integrated with the sensory data using a series of exploratory and predictive multivariate statistical ...

Based Detection, Linguistic Biomarkers, Machine Learning, Explainable AI, Cognitive Decline Monitoring Share and Cite: de Filippis, R. and Al Foysal, A. (2025) Early Alzheimer’s Disease Detection from ...

Michael O. Lawanson, a Nigerian data scientist at the University of Arkansas, United States, is at the forefront of global ...