Machine learning for health data science, fuelled by proliferation of data and reduced computational costs, has garnered ...

Researchers sought to determine an effective approach to predict postembolization fever in patients undergoing TACE.

AI agents help businesses stop guessing — linking predictions to actions so teams can move from “what might happen” to ...

Read more about AI-driven learning analytics struggle to deliver measurable gains in higher education on Devdiscourse ...

Heart specialists at Mayo Clinic today presented new research at the 2026 Society of Thoracic Surgeons Annual Meeting that ...

QA teams now use machine learning to analyze past test data and code changes to predict which tests will fail before they run. The technology examines patterns from previous test runs, code commits, ...

A new analysis of gene expression in blood samples suggests that specific biological signs of Parkinson’s disease are ...

LLMs tend to lose prior skills when fine-tuned for new tasks. A new self-distillation approach aims to reduce regression and ...

Machine learning is an essential component of artificial intelligence. Whether it’s powering recommendation engines, fraud detection systems, self-driving cars, generative AI, or any of the countless ...

Risk prediction has been used in the primary prevention of cardiovascular disease for >3 decades. Contemporary cardiovascular risk assessment relies on multivariable models, which integrate ...

BACKGROUND: BCR-ABL tyrosine kinase inhibitors (TKIs) have been increasingly linked to pulmonary arterial hypertension (PAH) since 2009, although supporting evidence is limited. Our objective was to ...

Background Motor and cognitive dysfunctions are common and disabling features in multiple sclerosis (MS) that remain challenging to treat. Here, we aimed to explore the effect of exergames as a ...