Sepsis is one of the most common and lethal syndromes encountered in intensive care units (ICUs), and acute respiratory failure (ARF) represents one of its most critical complications. Once ...

A machine learning model slightly outperforms a conventional regression model at predicting which children hospitalized for asthma will be readmitted within 180 days.

In people with type 1 diabetes (T1D), the immune system shuts down the body's ability to make the hormone insulin, ...

A new study offers insight into the health and lifestyle indicators—including diet, physical activity and weight—that align most closely with healthy brain function across the lifespan. The study used ...

A machine learning model analyzing CpG-based DNA methylation accurately predicted the origin of many different cancer types in patients with cancers of unknown primary (CUP), according to research ...

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 ...

In a National Institutes of Health (NIH)-funded study, researchers developed a cancer assessment tool that can identify high-risk patients and the tumor cells linked to that risk.

Machine learning models can predict the risk for developing moderate-to-severe persistent asthma and allergic rhinitis in children with early-life AD.

Researchers at the University of Oregon have developed an artificial intelligence tool that can read genetic code the way ...