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 ...

Williams, A. and Louis, L. (2026) Cumulative Link Modeling of Ordinal Outcomes in the National Health Interview Survey Data: Application to Depressive Symptom Severity. Journal of Data Analysis and ...

Discover the best DevOps automation tools for startups in 2025. Explore powerful solutions that enhance development speed, reliability, and collaboration, making your startup agile and competitive in ...

The effectiveness of Germany's gambling framework is currently being evaluated, and the regulator has now vowed to choose ...

The opposition leader of Ireland's Labour Party has called for the ban of all gambling advertisements in the country, but ...

Getting good at LeetCode Java can feel like a puzzle sometimes, right? You see all these problems, and you’re not sure where ...

How CPU-based embedding, unified memory, and local retrieval workflows come together to enable responsive, private RAG ...

Not only has Google's Gemini 3 model been trained on the company's own TPUs, but I've been using a MacBook Pro with Apple's M4 Pro chip for almost a year, and in that time, I've come to find the ...

You can stop looking for glitches in the Matrix—it’s finally been proven that our universe is not merely a simulation running on some powerful alien civilization’s supercomputer. An international team ...

Objectives: This study aims to investigate the efficacy of unsupervised machine learning algorithms, specifically the Gaussian Mixture Model (GMM), K-means clustering, and Otsu automatic threshold ...

Dozens of machine learning algorithms require computing the inverse of a matrix. Computing a matrix inverse is conceptually easy, but implementation is one of the most challenging tasks in numerical ...