Phys.org

Machine learning automates material analysis and design using X-ray spectroscopy data

Understanding the properties of different materials is an important step in material design. X-ray absorption spectroscopy (XAS) is an important technique for this, as it reveals detailed insights ...
Science Daily

'Democratizing chemical analysis':Chemists use machine learning and robotics to identify chemical compositions from images

Chemists have created a machine learning tool that can identify the chemical composition of dried salt solutions from an image with 99% accuracy. By using robotics to prepare thousands of samples and ...
Phys.org

Machine learning uses X-ray diffraction data from polymers to predict the behavior of new materials

Polymers such as polypropylene are fundamental materials in the modern world, found in everything from computers to cars. Because of their ubiquity, it's vital that materials scientists know exactly ...

From Brain Waves to Intelligent Insights: How Artificial Intelligence Is Transforming Neural Signal Analysis

Brain activity is commonly studied across frequency ranges such as delta, theta, alpha, beta, and gamma. These signals are complex, noisy, and non-stationary, and they can be affected by eye movements ...
Medical Xpress

Integrating machine learning with statistical methods enhances disease risk prediction models

Researchers from Peking University have conducted a comprehensive systematic review on the integration of machine learning into statistical methods for disease risk prediction models, shedding light ...
American Institute of Physics

Algorithm optimizes machine learning techniques that use linear, tunable resistor networks

Framework applying Kirchoff’s laws of current flow and voltage changes across circuits can identify lower-energy analog ...