Diagnostic screening programs help catch cancer, abnormalities or other diseases before they reach an advanced stage, saving lives and healthcare costs. Screening programs include, lung, breast, prostate, and cervical cancer, among many others.
New findings support the routine use of deep learning-based risk assessments, as this method can decrease subjectivity, reduce unnecessary imaging and improve diagnostic accuracy.
The COlorectal Cancer detection with AI, or COCA, model is a cost-effective, scalable solution that turns routine CT scans into opportunistic exams that can be used to proactively identify CRC.
Two respected radiology organizations have issued a stark warning on the new recommendations, stating that they risk confusing patients and “may contribute to thousands of additional breast cancer deaths each year.”
The Rutgers Center for Advanced Human Brain Imaging Research houses a state-of-the-art 3T MRI scanner that will help investigate Alzheimer's disease, addiction, and other conditions.
Body composition assessments are readily available in most clinics and may help doctors take early action in high-risk patients, according to a new study published in RSNA's journal Radiology.
Experts from Australia and the U.K. said strategies to improve reporting are "urgently" needed in order for the public to receive more balanced information.
Emory University researchers looked at data from more than 450,000 people diagnosed with Alzheimer's disease or vascular dementia for their findings, shared in AJR.