A team of experts determined that correlating masses initially detected on MRI are significantly more likely to result in a cancer diagnosis than other common findings.
The model incorporates specific data from MRI exams with patient risk factors to predict whether a person is likely to develop clinically significant prostate cancer.
Finely tuned, pre-trained large language models are beginning to reliably translate image content into text, but are they ready to take on medical images?