On the Opportunities and Risks of Foundation Models for Natural Language Processing in Radiology
2022; Radiological Society of North America; Volume: 4; Issue: 4 Linguagem: Inglês
10.1148/ryai.220119
ISSN2638-6100
AutoresWalter F. Wiggins, Ali S. Tejani,
Tópico(s)Radiomics and Machine Learning in Medical Imaging
ResumoHomeRadiology: Artificial IntelligenceVol. 4, No. 4 PreviousNext CommentaryOn the Opportunities and Risks of Foundation Models for Natural Language Processing in RadiologyWalter F. Wiggins , Ali S. TejaniWalter F. Wiggins , Ali S. TejaniAuthor AffiliationsFrom the Department of Radiology, Duke University Health System, 2301 Erwin Rd, Durham, NC 27710 (W.F.W.); Duke Center for Artificial Intelligence in Radiology, Duke University School of Medicine, Durham, NC (W.F.W.); and Department of Radiology, University of Texas Southwestern Medical Center, Dallas, Tex (A.S.T.).Address correspondence to W.F.W. (email: [email protected]).Walter F. Wiggins Ali S. TejaniPublished Online:Jul 20 2022https://doi.org/10.1148/ryai.220119MoreSectionsFull textPDF ToolsImage ViewerAdd to favoritesCiteTrack CitationsPermissionsReprints ShareShare onFacebookTwitterLinked In References1. Linna N, Kahn CE Jr. Applications of natural language processing in radiology: A systematic review. Int J Med Inform 2022;163:104779. Crossref, Medline, Google Scholar2. Vaswani A, Shazeer NM, Parmar N, et al. Attention is all you need. arXiv:1706.03762 [preprint] https://arxiv.org/abs/1706.03762. Posted June 12, 2017. Accessed June 15, 2022. Google Scholar3. Devlin J, Chang M, Lee K, Toutanova K. BERT: Pre-training of deep bidirectional transformers for language understanding. arXiv:1810.04805 [preprint] https://arxiv.org/abs/1810.04805. Posted October 11, 2018. Accessed June 15, 2022. Google Scholar4. Huang K, Altosaar J, Ranganath R.. ClinicalBERT: Modeling Clinical notes and predicting hospital readmission. arXiv:1904.05342 [preprint] https://arxiv.org/abs/1904.05342. Posted April 10, 2019. Accessed June 15, 2022. Google Scholar5. Wiggins WF, Kitamura F, Santos I, Prevedello LM. Natural language processing of radiology text reports: interactive text classification. Radiol Artif Intell 2021;3(4):e210035. Link, Google Scholar6. 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Google ScholarArticle HistoryReceived: June 17 2022Revision requested: June 19 2022Revision received: June 23 2022Accepted: June 27 2022Published online: July 20 2022 FiguresReferencesRelatedDetailsCited ByMachine Learning for Precision Epilepsy SurgeryLaraJehi2023 | Epilepsy CurrentsThe role of artificial intelligence in the differential diagnosis of wheezing symptoms in childrenLanSong, ZhenchenZhu, GeHu, XinSui, WeiSong, ZhengyuJin2022 | Radiology Science, Vol. 1, No. 1Applying BERT for Early-Stage Recognition of Persistence in Chat-Based Social Engineering AttacksNikolaosTsinganos, PanagiotisFouliras, IoannisMavridis2022 | Applied Sciences, Vol. 12, No. 23Accompanying This ArticleRadBERT: Adapting Transformer-based Language Models to RadiologyJun 15 2022Radiology: Artificial IntelligenceEpisode 23: NLP/Transformer Models for RadiologyOct 7 2022Default Digital Object SeriesRecommended Articles Natural Language Processing of Radiology Text Reports: Interactive Text ClassificationRadiology: Artificial Intelligence2021Volume: 3Issue: 4Current Applications and Future Impact of Machine Learning in RadiologyRadiology2018Volume: 288Issue: 2pp. 318-328RadBERT: Adapting Transformer-based Language Models to RadiologyRadiology: Artificial Intelligence2022Volume: 4Issue: 4Moving from ImageNet to RadImageNet for Improved Transfer Learning and GeneralizabilityRadiology: Artificial Intelligence2022Volume: 4Issue: 5Preparing Medical Imaging Data for Machine LearningRadiology2020Volume: 295Issue: 1pp. 4-15See More RSNA Education Exhibits Seeing Through the Eyes (and Visual Cortex) of a Machine: Convolutional Neural Networks at the Forefront of Machine Intelligence in Medical ImagingDigital Posters2018A Cased-Based Health Equity Primer for Radiologists: Real Cases, Real Problems, Real SolutionsDigital Posters2020Anatomy of a Deep Learning Project for Breast Cancer Prognosis Prediction: From Collecting Data to Building a PipelineDigital Posters2019 RSNA Case Collection Invasive ductal carcinoma of the breastRSNA Case Collection2020Pancreatic Schwannoma RSNA Case Collection2021COVID-19 pneumoniaRSNA Case Collection2020 Vol. 4, No. 4 PodcastMetrics Downloaded 181 times Altmetric Score PDF download
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