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Mashup Score: 48
“Just Accepted” papers have undergone full peer review and have been accepted for publication in Radiology: Artificial Intelligence. This article will undergo copyediting, layout, and proof review before it is published in its final version. Please note that during production of the final copyedited article, errors may be discovered which could affect the content. The Radiological Society of North of America (RSNA) and the Medical Image Computing and Computer Assisted Intervention (MICCAI) Society have led a series of joint panels and seminars focused on the present impact and future directions of artificial intelligence (AI) in radiology. These conversations have collected viewpoints from multidisciplinary experts in radiology, medical imaging, and machine learning on the current clinical penetration of AI technology in radiology, and how it is impacted by trust, reproducibility, explainability, and accountability. The collective points—both practical and philosophical—define the cult
Source: pubs.rsna.orgCategories: General Medicine News, Future of MedicineTweet
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Mashup Score: 2Checklist for Artificial Intelligence in Medical Imaging (CLAIM): 2024 Update | Radiology: Artificial Intelligence - 8 month(s) ago
To address the rapid evolution of artificial intelligence in medical imaging, the authors present the Checklist for Artificial Intelligence in Medical Imaging (CLAIM) 2024 Update.
Source: pubs.rsna.orgCategories: General Medicine News, Future of MedicineTweet
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Mashup Score: 3RadBERT: Adapting Transformer-based Language Models to Radiology | Radiology: Artificial Intelligence - 8 month(s) ago
Purpose To investigate if tailoring a transformer-based language model to radiology is beneficial for radiology natural language processing (NLP) applications. Materials and Methods This retrospective study presents a family of bidirectional encoder representations from transformers (BERT)–based language models adapted for radiology, named RadBERT. Transformers were pretrained with either 2.16 or 4.42 million radiology reports from U.S. Department of Veterans Affairs health care systems nationwide on top of four different initializations (BERT-base, Clinical-BERT, robustly optimized BERT pretraining approach [RoBERTa], and BioMed-RoBERTa) to create six variants of RadBERT. Each variant was fine-tuned for three representative NLP tasks in radiology: (a) abnormal sentence classification: models classified sentences in radiology reports as reporting abnormal or normal findings; (b) report coding: models assigned a diagnostic code to a given radiology report for five coding systems; and (c
Source: pubs.rsna.orgCategories: General Medicine News, Future of MedicineTweet
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Mashup Score: 2Checklist for Artificial Intelligence in Medical Imaging (CLAIM): 2024 Update | Radiology: Artificial Intelligence - 8 month(s) ago
To address the rapid evolution of artificial intelligence in medical imaging, the authors present the Checklist for Artificial Intelligence in Medical Imaging (CLAIM) 2024 Update.
Source: pubs.rsna.orgCategories: General Medicine News, Future of MedicineTweet
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Mashup Score: 2Checklist for Artificial Intelligence in Medical Imaging (CLAIM): 2024 Update | Radiology: Artificial Intelligence - 9 month(s) ago
To address the rapid evolution of artificial intelligence in medical imaging, the authors present the Checklist for Artificial Intelligence in Medical Imaging (CLAIM) 2024 Update.
Source: pubs.rsna.orgCategories: General Medicine News, Future of MedicineTweet
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Mashup Score: 7Assistive AI in Lung Cancer Screening: A Retrospective Multinational Study in the United States and Japan | Radiology: Artificial Intelligence - 9 month(s) ago
Purpose To evaluate the impact of an artificial intelligence (AI) assistant for lung cancer screening on multinational clinical workflows. Materials and Methods An AI assistant for lung cancer screening was evaluated on two retrospective randomized multireader multicase studies where 627 (141 cancer-positive cases) low-dose chest CT cases were each read twice (with and without AI assistance) by experienced thoracic radiologists (six U.S.-based or six Japan-based radiologists), resulting in a total of 7524 interpretations. Positive cases were defined as those within 2 years before a pathology-confirmed lung cancer diagnosis. Negative cases were defined as those without any subsequent cancer diagnosis for at least 2 years and were enriched for a spectrum of diverse nodules. The studies measured the readers’ level of suspicion (on a 0–100 scale), country-specific screening system scoring categories, and management recommendations. Evaluation metrics included the area under the receiver op
Source: pubs.rsna.orgCategories: General Medicine News, Future of MedicineTweet
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Mashup Score: 3Efficient Health Care: Decreasing MRI Scan Time - 10 month(s) ago
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Source: pubs.rsna.orgCategories: General Medicine News, Future of MedicineTweet
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Mashup Score: 2Radiology: Artificial Intelligence - 10 month(s) ago
Can’t sign in? Forgot your password? If the address matches an existing account you will receive an email with instructions to reset your password. Can’t sign in? Forgot your username? by Tugba Akinci D’Antonoli, MD and Merel Huisman, MD, PhD The May 2024 edition of the journal’s “#RadAIchat” tweet chat, titled “Medical AI Regulations: A Primer & Future Directions,” featured an expert panel: The chat aimed to untangle the complexities of medical AI regulations. As AI systems become increasingly integrated
Source: pubs.rsna.orgCategories: General Medicine News, Future of MedicineTweet
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Mashup Score: 3Efficient Health Care: Decreasing MRI Scan Time - 10 month(s) ago
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Source: pubs.rsna.orgCategories: General Medicine News, Future of MedicineTweet
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Mashup Score: 3Efficient Health Care: Decreasing MRI Scan Time - 10 month(s) ago
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Source: pubs.rsna.orgCategories: General Medicine News, Future of MedicineTweet
Read the perspectives of experts from @MICCAI_Society and @RSNA on the clinical, cultural, computational, and regulatory considerations to adopt #AI technology successfully in radiology https://t.co/CsPEVa2O1R #AIME2024 https://t.co/65dpqNd7cy