8 Apps for Radiologists
Apps that can help you perform your best.
With patient volume continuing to grow throughout healthcare-and the steady stream of referrals coming your way-it can feel as if your work as a radiologist is never done. At one time, that meant you spent countless hours tethered to your workstation, trapped in a dark reading room.Today, however, with the advent of the smartphone and the development of ever-sophisticated apps, you can stay on top of your workload and provide a high level of patient care from virtually anywhere. Diagnostic Imaging reviewed eight apps designed to keep you connected with your patients, your referring providers, and your facilities. The overall goal is to keep work at your fingertips while helping you be as productive and integrated as possible.
Possible Real-Time Adaptive Approach to Breast MRI Suggests ‘New Era’ of AI-Directed MRI
June 3rd 2025Assessing the simulated use of AI-generated suspicion scores for determining whether one should continue with full MRI or shift to an abbreviated MRI, the authors of a new study noted comparable sensitivity, specificity, and positive predictive value for biopsies between the MRI approaches.
Mammography Study Compares False Positives Between AI and Radiologists in DBT Screening
May 8th 2025For DBT breast cancer screening, 47 percent of radiologist-only flagged false positives involved mass presentations whereas 40 percent of AI-only flagged false positive cases involved benign calcifications, according to research presented at the recent American Roentgen Ray Society (ARRS) conference.
The Reading Room: Artificial Intelligence: What RSNA 2020 Offered, and What 2021 Could Bring
December 5th 2020Nina Kottler, M.D., chief medical officer of AI at Radiology Partners, discusses, during RSNA 2020, what new developments the annual meeting provided about these technologies, sessions to access, and what to expect in the coming year.
Study Assesses Potential of Seven-Minute AI-Enhanced 3T MRI of the Shoulder
February 20th 2025Researchers found that the use of seven-minute threefold parallel imaging-accelerated deep learning 3T MRI had 89 percent sensitivity for supraspinatus-infraspinatus tendon tears and 93 percent sensitivity for superior labral tears.
