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 ...
More accurate and individualized health predictions will allow for preventative factors to be implemented well in advance.
Morning Overview on MSNOpinion
Firms hire AI specialists over data engineers, and it’s backfiring
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: ...
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 ...
The Punch on MSN
At the intersection of AI, engineering, and human learning
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 ...
Abstract: Model predictive torque control (PTC) is a high-performance control strategy for induction motor (IM) drives. However, its performance is highly dependent on the motor parameters. Besides, ...
In this example, we demonstrate how to model power electronics devices that perform current control using MathWorks products, focusing on: The modeling style introduced in this example is not a ...
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