Researchers have developed a cost-effective technique for breast cancer screening that does not require radiation exposure.

Numerous deep learning models can detect and classify imaging findings with a performance that rivals human radiologists. However, according to a new study published in the Journal of the American College of Radiology, many of these AI models aren’t nearly as impressive when applied to external data sets.

AI models can be trained to predict outcomes in meningioma patients, according to new research published in npj Digital Medicine. The study’s authors even developed a free smartphone app so others can explore their work.

Deep learning-based AI models can improve the segmentation of white matter in 18F-FDG PET/CT images, according to a new study published in the Journal of Digital Imaging. This helps radiologists with the early diagnosis of neurodegenerative disease.

Caption Health, a California-based AI company, has received authorization from the FDA to market its software solution for acquiring echocardiography images in the United States.

AI algorithms can help radiologists achieve a “significant improvement” in their ability to detect breast cancer, according to a new study published in The Lancet Digital Health.

Chun Yuan, PhD, has received a two-year, $200,000 grant from the American Heart Association’s Institute for Precision Cardiovascular Medicine for his work on using AI to detect blocked arteries and cardiovascular risk.

Researchers have developed a multitask deep learning model that can effectively assess signs of hip osteoarthritis in x-rays, sharing their findings in Radiology.

Researchers out of Wuhan, China, have developed a new AI-based quality improvement system for colonoscopies, sharing their findings in The Lancet: Gastroenterology & Hepatology.

AI is making a monumental impact on the way radiologists and other imaging specialists deliver care, but some providers still can’t afford to make the necessary investments at this time.  

Researchers have developed a new quantitative framework that evaluates thyroid nodules at a level comparable to two expert radiologists.

Deep learning-based reconstruction (DLR) can reduce the radiation dose associated with low-dose chest and abdominal CT scans without sacrificing image quality, according to a new study published in the American Journal of Roentgenology.

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