Researchers sought to determine an effective approach to predict postembolization fever in patients undergoing TACE.

Among patients with chronic noncancer pain, a novel machine learning model effectively predicts opioid use disorder risk.

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, ...

Please provide your email address to receive an email when new articles are posted on . The best model for predicting schizophrenia performed substantially better than the best bipolar ...

A team of researchers has successfully predicted abnormal grain growth in simulated polycrystalline materials for the first time -- a development that could lead to the creation of stronger, more ...

A machine learning model incorporating functional assessments predicts one-year mortality in older patients with HF and improves risk stratification beyond established scores. Functional status at ...

The severity of symptoms in posttraumatic stress disorder (PTSD) varies greatly across individuals in the first year after trauma and it remains difficult to predict whether someone might worsen, ...

COMET, a novel machine learning framework, integrates EHR data and omics analyses using transfer learning, significantly enhancing predictive modeling and uncovering biological insights from small ...

Researchers claim model can cut years from testing cycles Scientists have developed a machine learning method that could ...

Local factors such as seasonal temperature, the year-dependent water and vegetation index, and data on animal density can be used to predict regional outbreaks of avian flu in Europe. This is the ...