Researchers at MUSC Hollings Cancer Center have developed a machine learning tool to identify cancer patients who may be at high risk for financial toxicity – the financial stress and hardship that ...

Enhancing Readability of Lay Abstracts and Summaries for Urologic Oncology Literature Using Generative Artificial Intelligence: BRIDGE-AI 6 Randomized Controlled Trial We trained and tested ML systems ...

A machine-learning model developed by Weill Cornell Medicine investigators may provide clinicians with an early warning of a complication that can occur late in pregnancy. Preeclampsia is a sudden ...

Two complementary predictors (DAAE-M and ELIE) estimate individualized 5-year progression risk using routine clinical data, extending the prior DAAE framework beyond static baseline risk. Registry ...

Millions of people are diagnosed with Alzheimer's disease each year, comprising 60% to 70% of dementia cases worldwide. While cognitive impairment and structural brain changes are indicative of ...

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 ...

A machine learning model uses cloud type and cloud cover to predict rapid changes in surface solar irradiance, including short-term “ramp” events that affect grid stability. When tested across 15 ...

illustrating the comprehensive zero-shot benchmark of 19 universal machine learning interatomic potentials and the dominant impact of training data composition for surface energy prediction. A ...

Blood pressure is a key metric of cardiovascular health, but standard methods for measuring it rely on occasional readings ...