Can AI make heart failure evidence reviews faster and more reliable? New iCARE4CVD research puts it to the test
Screening thousands of research papers is one of the most time-consuming steps in evidence synthesis. A new study from the iCARE4CVD consortium asks whether large language models can do it reliably — and at scale.
Prediction or speculation: heart failure models for diabetes – An Editorial comment from iCARE4CVD
Can we predict heart failure in people with diabetes, or are we merely speculating? That is the question explored in a recent iCARE4CVD editorial, which discusses a large meta-analysis evaluating more than 50 prediction models designed to identify individuals with type 2 diabetes who are at risk of developing heart failure or being hospitalised because of it.
