A team of researchers from the University of Chicago's Pritzker School of Molecular Engineering (UChicago PME) has used ...

A machine learning lung cancer risk prediction model outperformed logistic regression, supporting improved risk assessment and more efficient radiology based lung cancer screening.

n this study, 773 untreated breast cancer patients from all over China were collected and followed up for at least 5 years. We obtained clinical data from 773 cases, RNA sequencing data from 752 cases ...

For the first time, researchers have used machine learning – a type of artificial intelligence (AI) – to identify the most important drivers of cancer survival in nearly all the countries in the world ...

UT biochemistry major Milit Patel collaborated with researchers at Memorial Sloan Kettering Cancer Center on research published in a top cancer journal.

AI has revealed why cancer survival differs so dramatically around the world, highlighting the specific health system factors that matter most in each country.

The SleepFM model reveals how sleep analysis can predict disease risk, offering insights into sleep's role as a vital health ...