The new research, presented during ARRS 2024 in Boston, suggests CVD risk models may need to include certain findings identified in routine mammograms.
The goal of the study is to obtain quantitative data on how daily training and competing affect players’ musculoskeletal health. The information will be used to inform training, rest and recovery periods.
Experts argue that the overall incidence of blunt cerebrovascular injury is very low and that symptomatic vascular injuries in these cases are even lower.
The deep learning model was trained to predict risk of lung cancer in the one to six years following completion of an LDCT scan, and it does not require clinical information relative to risk factors to do so.
While there are numerous formulas to help guide providers in managing incidental findings, there is limited data available on the outcomes and cost-effectiveness of the subsequent evaluations that follow.
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.
