Tech Times

AI-Generated Market Forecasting: How Predictive Analytics Accelerate Strategic Planning

AI market forecasting uses predictive analytics and strategic planning tools to anticipate demand shifts, optimize decisions, ...
European Medical Journal

Machine Learning Shows Promise in Predicting RA Treatment Response

A scoping review shows machine learning models may help predict response to biologic and targeted synthetic DMARDs in ...
Semiconductor Engineering

Accelerating Semiconductor Innovation Through Machine Learning-Driven Modeling

Using AI and machine learning as transformative solutions for semiconductor device modeling and parameter extraction.
Devdiscourse

AI and Industrial IoT join forces to power next-gen predictive maintenance

In AIoT-based systems, sensors continuously collect high-frequency data such as vibration, temperature, pressure, and electrical signals. These data streams are processed by machine learning and deep ...

Predictive Modeling: Techniques, Uses, and Key Takeaways

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

Designing AI Agents for Predictive Maintenance in Energy Infrastructure

AI agents for predictive maintenance in energy infrastructure help cut downtime and boost efficiency. Discover how to design ...
Scientific Research Publishing

Reinforcement Learning for Antidepressant Dose Adjustment: An Explainable Agent Approach ()

Reinforcement Learning, Explainable AI, Computational Psychiatry, Antidepressant Dose Optimization, Major Depressive Disorder, Treatment Personalization, Clinical Decision Support Share and Cite: de ...
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 ...