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

Engaging System 2 requires significant metabolic energy. Your brain consumes a lot of your body’s energy as it is; intense ...

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 ...

Learn how a free tool lets you build and test digital circuits on your computer and see how chips really work before making ...

Learn what is Linear Regression Cost Function in Machine Learning and how it is used. Linear Regression Cost function in ...

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 ...

Today's AI agents are a primitive approximation of what agents are meant to be. True agentic AI requires serious advances in reinforcement learning and complex memory.

One of the most overlooked aspects of AI tools for CAS is how simple tweaks can make a huge difference on the bottom line and ...

This important study combines optogenetic manipulations and wide-field imaging to show that the retrosplenial cortex controls behavioral responses to whisker deflection in a context-dependent manner.

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 ...

Where does artificial intelligence (AI) live in the physical world? Not in the cloud, but in industrial vaults of silicon and steel. Its life depends on the same electrical grids that power our cities ...

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 ...