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?
Eric Secemsky, MD, from Beth Israel Deaconess Medical Center and Harvard Medical School, says a lack of hands-on training and reimbursement challenges are hindering the adoption of IVUS.
Automated AI-generated measurements combined with annotated CT images can improve treatment planning and help referring physicians and patients better understand their disease, explained Sarah Jane Rinehart, MD, director of cardiac imaging with Charleston Area Medical Center.
Two advanced algorithms—one for CAC scores and another for segmenting cardiac chamber volumes—outperformed radiologists when assessing low-dose chest CT scans.
"Gen AI can help tackle repetitive tasks and provide insights into massive datasets, saving valuable time," Thomas Kurian, CEO of Google Cloud, said Tuesday.
