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A semiautonomous deep learning system reduced the number of screening mammograms requiring radiologist interpretation (Pedemonte et al).
Transfer learning and self-supervised cross-training improved classification of pediatric low-grade glioma (Tak and Ye et al).
AI model showed better diagnostic accuracy than radiologists, as well as reduced reading times (Park et al). See commentary by Bae.
Exploring an AI system for screening mammography to identify patients at highest risk for breast cancer (Larsen et al). See commentary by Bahl and Do.
A deep learning approach successfully analyzed brain structures most affected in patients with progressive supranuclear palsy (Nigro et al). See commentary by Mohajer.
An assistive AI tool for lung cancer screening improved specificity of radiologists in the United States and Japan (Kiraly et al).
Deep learning MRI reconstruction methods reduced scanner and room times in a clinical setting (Yang et al). See commentary by GharehMohammadi and Sebro.