The Lancet

When to and when not to use machine learning in risk prediction models

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 ...
Communications of the ACMOpinion

When AI Tools Train on AI Output: Model Collapse in Daily Workflows

The degradation is subtle but cumulative. Tools that release frequent updates while training on datasets polluted with ...
AHA/ASA Journals

Criteria to Assess the Predictive and Clinical Utility of Novel Models, Biomarkers, and Tools for Risk of Cardiovascular Disease: A Scientific Statement From the American Heart ...

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 ...

These Mathematicians Are Putting A.I. to the Test

Large language models struggle to solve research-level math questions. It takes a human to assess just how poorly they ...

AI model reads brain MRIs in seconds, hitting up to 97.5% accuracy

An AI-powered model developed at the University of Michigan can read a brain MRI and diagnose a person in seconds, a study suggests. The model detected neurological conditions with up to 97.5% ...