Researchers sought to determine an effective approach to predict postembolization fever in patients undergoing TACE.
A recent study on the development and validation of an AI-based framework for first-trimester preeclampsia risk assessment ...
Background Current diagnosis of antiphospholipid syndrome (APS) relies on antiphospholipid antibodies (aPL) testing, but false-positive aPL results and asymptomatic aPL carriers pose significant ...
The Southern Maryland Chronicle on MSN
How are QA teams using machine learning to predict test failures in real time?
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, ...
Objectives To describe the incidence, presentation and long-term health outcomes of suicidal thoughts and behaviours (STBs) in children aged 12 years or under. Methods This population-based study ...
Machine learning for health data science, fuelled by proliferation of data and reduced computational costs, has garnered ...
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 ...
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 ...
In this nationwide cohort study, trans Australians experienced substantially elevated mortality risk. Tailored policy responses are needed to address premature mortality in trans populations.
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