BMJ Open

Using virtual twin-based AI models to detect atrial fibrillation and improve stroke outcomes [TAILOR]: a multicentre prospective cohort study

Introduction Atrial fibrillation (AF) is the leading cause of cardioembolic stroke and is associated with increased stroke severity and fatality. Early identification of AF is essential for adequate ...
Scientific Research Publishing

Early Alzheimer’s Disease Detection from Short Speech Samples Using Lightweight, Interpretable Linguistic Markers ()

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 ...
Tech Xplore

Machine learning helps robots see clearly in total darkness using infrared

From disaster zones to underground tunnels, robots are increasingly being sent where humans cannot safely go. But many of ...
TechAnnouncer

Mastering AI Training Courses: Your Guide to Top Programs in 2026

While some AI courses focus purely on concepts, many beginner programs will touch on programming. Python is the go-to ...
IEEE

Machine Learning Techniques for Stock Market Prediction: Neural Networks and Soft Computing Approaches

Abstract: This paper provides an updated overview of recent literature on stock market prediction using machine learning methods. Neural network-based models, particularly those focused on predicting ...
IEEE

Reviving Legacy Seismic Data via Machine Learning Technique—Part 2: Estimating 3-D Seismic Volumes From 2-D Seismic Lines With VQ-VAE

Abstract: We propose a machine learning-based method that estimates a 3-D seismic volume from irregularly placed 2-D seismic lines, addressing the challenges regarding the local disturbances contained ...