The study is the first, and largest of it's kind, according to researchers from the University College London, and offers new insights into how the heart functions.
Discussing discordant findings on breast cancer screening exams improves care, and international experts believe the U.S. should reconsider its "single-reader paradigm," they wrote in Radiology.
A Seattle-based researcher dramatically reduced the time necessary to read a scan from four hours down to seven minutes.
One expert believes AI "simply isn't ready" to handle the ever-growing workload many imaging professionals are encountering, sharing his thoughts Feb. 4 in Forbes.
More than 230 million people are impacted by osteoarthritis across the globe, and that figure is only increasing in the United States as the population grows older.
The deep learning model can identify parasites that cause the disease in blood sample images as accurately as human experts, but in a fraction of the time, researchers wrote in the Journal of Digital Imaging.
Two researchers found that using certain pixel dimensions helped tailor algorithms to detect specific abnormalities, and pushed radiology to keep this in mind when using such approaches.
Japan-based researchers believe the algorithm can illuminate "hidden" information contained in imaging exams, and help radiologists in their clinical decision-making.
That's according to a recent white paper published by the American Society of Radiologic Technologists.
Experts believe their approach will allow specialists to pinpoint brain-related pathologies—such as physical injuries, cancer or language disorders, among other things—with improved accuracy.
This most recent approval marks the fourth of its kind for Tel Aviv, Israel-based Aidoc.
AI trained and tested on more than 8,000 biopsies was nearly perfect at spotting differences in samples with or without cancer.