Insulin resistance - when the body doesn't properly respond to insulin, a hormone that helps control blood glucose levels - ...

Machine learning for health data science, fuelled by proliferation of data and reduced computational costs, has garnered ...

The researchers suggest that this improvement in diagnostic performance for OFC biomarker discovery can be used to develop a diagnostic alternative for food allergy that is scalable and more efficient ...

Georgia Tech’s Qi Tang is building machine learning (ML) models to accelerate nuclear fusion research, making it more affordable and more accurate. Backed by a grant from the U.S. Department of Energy ...

Microelectromechanical systems (MEMS) electrothermal actuators are widely used in applications ranging from micro-optics and microfluidics to nanomaterial testing, thanks to their compact size and ...

Hundreds of thousands of children in China have been separated from their parents. A Yale SOM study finds that a ...

In data analysis, time series forecasting relies on various machine learning algorithms, each with its own strengths. However, we will talk about two of the most used ones. Long Short-Term Memory ...

Orlando, US, February 10th, 2026, FinanceWireSMA Marketing announced the development of a new machine-learning–driven ...

Machine learning algorithms that output human-readable equations and design rules are transforming how electrocatalysts for ...

Lithium-ion batteries have become the quiet workhorses of the energy transition, but the way they are designed and tested has ...