Discover how multivariate models use multiple variables for investment forecasting, risk analysis, and decision-making in ...

Duah: Using puzzles, both at home and in classrooms, can restore the often-forgotten truth that learning happens in ...

Researchers have identified specific coupled patterns of brain activity and gene expression that help explain impulsive behavior in children with attention deficit hyperactivity disorder. By analyzing ...

Background Multiple long-term conditions (MLTCs) are common among individuals with heart failure (HF); however, the influence ...

Objective This study aims to assess the prevalence of cancer risk factors in China’s working population and provide evidence for formulating more targeted workplace cancer prevention strategies.

At the core of every AI coding agent is a technology called a large language model (LLM), which is a type of neural network ...

Marshall Hargrave is a stock analyst and writer with 10+ years of experience covering stocks and markets, as well as analyzing and valuing companies. Michael Boyle is an experienced financial ...

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 ...

The authors provide a useful integrated analytical approach to investigating MASLD focused on diverse multiomic integration methods. The strength of evidence for this new resource is solid, as ...

Jennifer Simonson is a business journalist with a decade of experience covering entrepreneurship and small business. Drawing on her background as a founder of multiple startups, she writes for Forbes ...

Background Cognitive impairment (CI) is one of the most common manifestations of neuropsychiatric systemic lupus ...

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 ...