Researchers have developed a new machine-learning-assisted approach to optimize micro-electro-discharge machining (µ-EDM) of ...

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 ...

In an interview with Technology Networks, Dr. Daniel Reker discusses how machine learning is improving data-scarce areas of drug discovery.

Relating brain activity to behavior is an ongoing aim of neuroimaging research as it would help scientists understand how the brain begets behavior — and perhaps open new opportunities for ...

The Opioid Risk Tool for Opioid Use Disorder may help identify patients with chronic noncancer pain at increased risk for OUD ...

The team utilized machine learning to analyze public data from the National Health and Nutrition Examination Survey.

Read more about AI-driven learning analytics struggle to deliver measurable gains in higher education on Devdiscourse ...

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

The ability to anticipate what comes next has long been a competitive advantage -- one that's increasingly within reach for developers and organizations alike, thanks to modern cloud-based machine ...

QA teams now use machine learning to analyze past test data and code changes to predict which tests will fail before they run. The technology examines patterns from previous test runs, code commits, ...