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 ...

Effect of incorporating symptom burden with mortality as a composite outcome on accuracy and bias in palliative care identification algorithms in oncology. This is an ASCO Meeting Abstract from the ...

Study of Over Three Million Patients for Risk of Type 2 Diabetes Demonstrates Potential for More Advanced Approach to Early Identification ...

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 ...

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 ...

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 ...

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 can ...

A new study shows that machine-learning models can accurately predict daily crop transpiration using direct plant measurements and environmental data. By training models on seven years of ...

A recent study published in npj Materials Degradation introduces a two-stage machine learning (ML) framework that predicts the degradation of protective coatings under various environmental conditions ...

People are exposed to thousands of chemicals every day—through the products they use, the food they eat and the environments they live in—but only a fraction of those chemicals have been fully tested ...