A machine learning model using routine clinical data more accurately predicted 5-year heart failure risk in patients with CKD ...

Sepsis is one of the most common and lethal syndromes encountered in intensive care units (ICUs), and acute respiratory ...

Among pediatric patients presenting to the emergency department (ED) with high fevers, pinpointing those at risk for developing sepsis “is akin to looking for a needle in the haystack,” said Elizabeth ...

Using a form of machine learning called self-supervised learning, Mass General Brigham researchers have created a new predictive artificial intelligence model, which they say could help generate ...

This predictive model built on readily acquired clinical data provides encouraging results for the detection of residual disease. External validation and prospective studies implementing the model in ...

We've been watching temperatures climb, extreme weather events intensify, and ice sheets shrink. Every weather forecast and climate projection relies on incredibly complex computer simulations that ...

Machine learning model predicts poor pain-related quality of life after endometriosis surgery to assist clinicians with preoperative counseling.

A poor night's sleep portends a bleary-eyed next day, but it could also hint at diseases that will strike years down the road. A new artificial intelligence model developed by Stanford Medicine ...

Using routine clinical data, the model gauges liver cancer risk better than existing tools, offering a potential way to identify high-risk patients missed by current screening criteria.