Artificial intelligence (AI), using a simple blood test combined with standard brain images has, for the first time, been ...

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 ...

Objective To characterise the age-related impact of organ damage patterns on health-related quality of life (HRQoL) in ...

A research team shows that phenomic prediction, which integrates full multispectral and thermal information rather than ...

By training statistical and machine-learning models to predict expert visual scores, the study demonstrates that phenomics can match or outperform ...

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 ...

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

This study provides important evidence that negative affect is associated with slower cognitive processing in daily life, with findings replicated across three independent samples and supported by ...

Abstract: The purpose of this study was to investigate the relationship between workload and in-game technical and athletic performance. To achieve this,A modeling approach that predicts multiple ...

Meet Mark Grebner, the Michigan statistician who helped pioneer the science of predicting whether someone will vote Republican or Democratic. By Thomas Fuller Reporting from East Lansing, Mich.