Palpable, Tender Breast Mass

Emphasizing multi-structure segmentation and feature extraction from chest CT scans, an emerging AI model demonstrated an approximately 70 percent AUC for predicting significant incidental extrapulmonary findings as well as two-year and 10-year all-cause mortality.

In the third episode of a three-part podcast, Anand Narayan, M.D., Ph.D., and Amy Patel, M.D., discuss the challenges of expanded breast cancer screening amid a backdrop of radiologist shortages and ever-increasing volume on radiology worklists.

Radiomics models offered a pooled AUC of 86 percent for differentiating between ruptured and unruptured intracranial aneurysms, according to a recently published meta-analysis.

In the second episode of a three-part podcast, Anand Narayan, M.D., Ph.D., and Amy Patel, M.D., discuss recent studies published by the Journal of the American Medical Association (JAMA) that suggested moving to more of a risk-adapted model for mammography screening.

Review the case and test your knowledge to make the correct diagnosis.

A machine-learning-based model demonstrated an 87 percent area under the curve and a 90 percent specificity rate for predicting interstitial lung abnormality on CT scans, according to new research.