Medical Imaging
Study finds radiologists and AI models struggle to spot AI-generated “deepfake” X-rays
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A study published March 24, 2026 in *Radiology* reports that AI-generated “deepfake” X-rays can be convincing enough to mislead radiologists and several multimodal AI systems. In testing, radiologists’ average accuracy rose from 41% when they were not told fakes were included to 75% when they were warned, highlighting potential risks for medical imaging security and clinical decision-making.
University of Missouri researchers report that a small antibody fragment targeting the EphA2 protein can be tagged with a radioactive marker to make EphA2-positive tumors stand out on PET scans in mouse experiments, a step they say could help match patients to EphA2-targeted therapies.
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Researchers at the University of Michigan have developed an AI system called Prima that interprets brain MRI scans in seconds, identifying neurological conditions with up to 97.5% accuracy. The tool also flags urgent cases like strokes and brain hemorrhages, potentially speeding up medical responses. Findings from the study appear in Nature Biomedical Engineering.