Radiology: Artificial Intelligence
@Radiology_AI
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The leading scientific journal on Artificial Intelligence in radiology, published by @RSNA. #AI #ArtificialIntelligence #MachineLearning #DeepLearning
Oak Brook, IL, USA
Joined November 2018
We're proud to welcome the journal's 2025-2027 Trainee Editorial Board! Learn more about these talented individuals:
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MammosighTR: a resource for advancing AI applications in breast cancer detection @suayipbirinci #dataset #breast #ML
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Combined image & feature space randomization for CT and MRI #segmentation model @csmcbiri #DeepLearning #ML #MachineLearning
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For breast ultrasound, an #AI system generated high-quality reports & helped junior radiologists improve diagnosis of BI-RADS categories @ShenzhenUni #BreastCancer #cancer #ML
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Retrieval-augmented generation offers potential to improve diagnostic accuracy, transparency & decision support @UniFreiburg #LLM #LargeLanguageModel #MachineLearning
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#AI-based model for real-time nuchal translucency plane identification and measurement in prenatal US assessments @ShenzhenUni #RadUS #sonogram #ML
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Special report equips professionals with strategies to mitigate cybersecurity challenges for safe use of LLMs in health care @ShahriarFaghani @BrdKhsrv @k_bressem #security #cyberattack #ML
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Deep learning method for lumbar paraspinal muscle segmentation on MRI @griffith_uni #MachineLearning #myosteatosis #AI
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Characterizing the Impact of Training Data on Generalizability: Application in Deep Learning to Estimate Lung Nodule Malignancy Risk @jacobscolin1 #cancer #training #CT
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Comprehensive overview of federated learning, privacy-preserving federated learning & uncertainty quantification in federated learning @MoffittNews #PPFL #MachineLearning #UQ
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RadioRAG retrieves context-specific information from #Radiopaedia in real-time @starasteh @DanielTruhn @laim_uka #NLP #RadioRAG #AI
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AI system uses breast US images to generate high-quality reports @ShenzhenUni #breast #BreastCancer #ML
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The MammosighTR dataset is derived from Türkiye’s national breast cancer screening program @suayipbirinci #mammography #cancer #ML
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AIM-NT model demonstrates high accuracy in identifying nuchal translucency plane and measuring thickness on prenatal US @ShenzhenUni #prenatal #sonogram #PedsRad
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Explore leading-edge research in Radiology: Artificial Intelligence. ➡️ @IJCAIconf #IJCAI2025 #AI #ArtificialIntelligence #MachineLearning #ML #DeepLearning
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Estimating Total Lung Volume from Pixel-Level Thickness Maps of Chest Radiographs Using Deep Learning @IJCAIconf #IJCAI2025 #AI #ArtificialIntelligence #MachineLearning
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