Final random-forest-based models outperformed all publicly available risk scores on internal and external test sets.

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

A machine learning model can accurately predict an individual’s risk of developing hepatocellular carcinoma (HCC) using routine clinical data, according to a new study. The findings point to a ...

Mount Sinai researchers have created an analytic tool using machine learning that can predict cardiovascular disease risk in patients with obstructive sleep apnea ...

Mount Sinai researchers have created an analytic tool using machine learning that can predict cardiovascular disease risk in ...

MASLD is prevalent in T2DM patients, with a 65% occurrence rate, and poses a higher risk for severe liver diseases. The study analyzed 3,836 T2DM patients, identifying key predictors like BMI, ...

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 ...

Infinite dilution activity coefficient is a key thermodynamic parameter in solvent design for chemical processes. Although ...

Researchers have used artificial intelligence to predict dozens of previously unknown carbon crystal structures, including at least one with a calculated hardness exceeding that of diamond. The ...