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 ...

LOS ANGELES, CA / ACCESS Newswire / December 22, 2025 / As businesses rush to automate everything from customer service to strategic planning, failure rates remain stubbornly high. Countless ...

Discover the power of predictive modeling to forecast future outcomes using regression, neural networks, and more for improved business strategies and risk management.

In May 2025, the U.S. Army’s Soldier Lethality Project at the Picatinny Arsenal in New Jersey announced the official type classification of SIG Sauer’s M7 rifle and M250 automatic rifle, previously ...

OBJECTIVE: Obesity is a global health problem. The aim is to analyze the effectiveness of machine learning models in predicting obesity classes and to determine which model performs best in obesity ...

The Recentive decision exemplifies the Federal Circuit’s skepticism toward claims that dress up longstanding business problems in machine-learning garb, while the USPTO’s examples confirm that ...

Logistic Regression is a widely used model in Machine Learning. It is used in binary classification, where output variable can only take binary values. Some real world examples where Logistic ...

1 San Juan Bautista School of Medicine, Caguas, Puerto Rico, United States 2 Independent Researcher, Monmouth County, NJ, United States Background: In many countries, patients with headache disorders ...

In the context of the rapid development of intelligent manufacturing, the stable operation of mechanical equipment is crucial for maintaining industrial production continuity and achieving economic ...

While many countries have registries of livestock farms, it can be challenging to obtain information on their primary production type. For example, for Swiss farms registered as keeping cattle, a ...