Top Five Ultrasound Content of 2024

Emerging research suggests that a deep learning model may offer 92 percent sensitivity in lung tumor detection on CT scans and up to a 59 percent reduction in tumor segmentation time.

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.

The IQ-UIP AI software may bolster computed tomography diagnosis of usual interstitial pneumonia (UIP), which is reportedly misdiagnosed in over 50 percent of cases.

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.

Survey results revealed that 71 percent of clinicians preferred adjunctive AI in facilitating triage of brain MRI scans and 58 percent were comfortable utilizing AI triage without input from radiologists.

Adjunctive AI offered greater than seven percent increases in sensitivity, specificity, and accuracy for ultrasound detection of ovarian cancer in comparison to unassisted clinicians who lacked ultrasound expertise, according to findings from new international multicenter research.