Depression is one of the most widespread mental health disorders worldwide, affecting approximately 4% of the global ...

For the first time, researchers have used machine learning—a type of artificial intelligence (AI)—to identify the most ...

Researchers developed a machine learning model that could identify children in the ED who were at risk for developing sepsis ...

Background Annually, 4% of the global population undergoes non-cardiac surgery, with 30% of those patients having at least ...

The XGBoost model predicts hyperglycemia risk in psoriasis patients with high accuracy, achieving an AUC of 0.821 in the training set. A web-based calculator was developed to facilitate personalized ...

Researchers worked with the Federal Reserve to create a predictive model that assesses hundreds of institutional ...

A new machine-learning-based approach to mapping real-time tumor metabolism in brain cancer patients, developed at the ...

Buildings produce a large share of New York's greenhouse gas emissions, but predicting future energy demand—essential for ...

Postpartum depression (PPD) affects up to 15 percent of individuals after childbirth. Early identification of patients at risk of PPD could improve proactive mental health support. Researchers ...

The ability to anticipate what comes next has long been a competitive advantage -- one that's increasingly within reach for developers and organizations alike, thanks to modern cloud-based machine ...