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 ...

Abstract: This study tackles the challenge of optimizing light emitting diode (LED) street lighting to enhance energy efficiency without compromising safety and comfort in dynamic urban environments.

More accurate and individualized health predictions will allow for preventative factors to be implemented well in advance.

Corporate leaders are racing to hire artificial intelligence talent, convinced that a few high-profile specialists can ...

This repository contains the code and documentation for a project that focuses on predicting stock market prices using LSTM models and optimizing a portfolio based on these predictions. Objective: ...

In this work we present two main contributions: the first one is a Python implementation of the discrete approximation of the Laplace-Beltrami operator (LBO) (Belkin et al., 2008) allowing us to solve ...

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

Test vendors use AI and machine learning to handle massive data volumes from complex electronics and detect hard-to-find ...

Abstract: The demonstrative realisation of this research is the smart health monitoring system, proposed and designed to employ wearable IoT technology and predictive analysis for constant health ...

Taiwo Feyijimi stands at a rare crossroads where advanced artificial intelligence, engineering education, and human learning converge. As a doctoral candidate in Engineering Education Transformations ...