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

Researchers have significantly enhanced an artificial intelligence tool used to rapidly detect bacterial contamination in ...

Machine learning for health data science, fuelled by proliferation of data and reduced computational costs, has garnered considerable interest among researchers. The debate around the use of machine ...

Objective To determine if communication disorders (1) increase the risk for common mental and physical health conditions and (2) if risk varies by age of onset (≤25 years (developmental) or >25 years ...

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, ...

Introduction Ischaemic heart disease (IHD) remains a leading cause of morbidity and mortality worldwide and poses an ...

Objective This study focused on the preferences for psychological assistance and associated factors among Chinese healthcare workers (HCWs) during the COVID-19 pandemic. Design Cross-sectional ...

An interdisciplinary research team has unveiled the world's first artificial intelligence (AI) model designed to classify both the cancer stage and risk category of thyroid cancer, achieving ...

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 ...

Here's a statistical challenge worthy of a grandmaster: How do you create an accurate ranking system when the best players ...

A novel artificial intelligence (AI) model accurately detected the presence of placenta accreta spectrum (PAS), a dangerous pregnancy condition that often goes undetected with current screening ...