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?
“Results of this case-control study suggest that even for maximum univariate biological differences, deviations between patients with MDD and healthy controls were remarkably small," experts shared in JAMA Psychiatry.
A new analysis offers a detailed comparison of soft-tissue lymphomas and soft-tissue tumors based on imaging characteristics from MRI scans—an area of study that has not yet been rigorously explored, the authors of the paper indicated.
When combined with artificial intelligence-based noise reduction techniques, new photon-counting CT technology can increase the detection of bone disease while also decreasing radiation exposure.
The event was the sixth Workshop on Medical Applications of Spectroscopic X-ray Detectors, which wrapped Sept. 1 at the largest particle physics lab in the world.
The effect shows up on functional MRI as increased brain activity in regions involved in pain, emotion and attention—not only during the procedure but also afterward, when patients remember the experience and score its discomfort level.
Six radiologists interpreting around 500 chest radiographs with an assist from AI bested unaided radiologists in measures of efficiency and/or accuracy in a new comparative performance study.
New research, published in JAMA Cardiology, challenges the common belief that AFib is more likely to develop among men than women. The key problem, it seems, is that prior research teams did not understand the significance of certain risk factors.
