Researchers successfully developed a machine learning-based method for predicting symptom deterioration in patients with cancer.

Kernel methods represent a cornerstone in modern machine learning, enabling algorithms to efficiently derive non-linear patterns by implicitly mapping data into high‐dimensional feature spaces. At the ...

Understanding the properties of different materials is an important step in material design. X-ray absorption spectroscopy ...

With the rapid advancements in computer technology and bioinformatics, the prediction of protein-ligand binding sites has ...

X-ray absorption spectroscopy (XAS) provides valuable information about a material’s properties and electronic states.

A scientist in Sweden has developed a new hybrid local features-based method using thermographs to identify faulty solar panels. A researcher from Sweden’s Jönköping University has proposed a machine ...

IOP Publishing’s Machine Learning series is the world’s first open-access journal series dedicated to the application and ...

Southwest Research Institute (SwRI) has developed a method to automate the calibration of heavy-duty diesel truck emissions ...

The research aim is to develop an intelligent agent for cybersecurity systems capable of detecting abnormal user behavior ...

Monoclonal antibody (mAb) manufacturing must continually improve to keep up with increasing demands. To do this, biomanufacturers can deploy machine learning tools to augment traditional process ...

Prediction of crystal structures of organic molecules is a critical task in many industries, especially in pharmaceuticals ...