Here, Ron Muscosky, worldwide product line manager at Carestream Health, sits down with AXIS Imaging News to discuss the surge of artificial intelligence technologies in medical imaging devices and what it means for clinicians—and the future of radiology.
A novel artificial intelligence blood testing technology was found to detect more than 90% of lung cancers in samples from nearly 800 individuals with and without cancer.
As artificial intelligence (AI) becomes increasingly integrated into clinical practice, the Radiological Society of North America is launching its Imaging AI Certificate program to deliver a pathway for radiologists to understand and learn how to apply AI to their radiology practices.
An artificial intelligence-driven system that automatically combs through brain MRIs for abnormalities could speed care to those who need it most, according to a study published in Radiology: Artificial Intelligence.
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In a study conducted by Finnish researchers, microscopic images of myelodysplastic syndrome patients’ bone marrow samples were examined utilizing an image analysis technique based on machine learning.
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In a March 5 letter, three radiology societies urged U.S. Department of Health and Human Services (HHS) officials to reject a “midnight” proposal by the immediate-past HHS Secretary to permanently exempt certain medical devices from the FDA’s 510(k) premarket notification requirements.
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Israel-based Aidoc announces the launch of an artificial intelligence-based automated activation solution that facilitates rapid risk assessment and care coordination for high-risk pulmonary embolism patients.
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A machine learning algorithm helps accurately differentiate benign and premalignant colorectal polyps on CT colonography scans, according to a study published in the journal Radiology.
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