The Future of AI and Informatics in Radiology: 10 Predictions

医学 信息学 放射科 医学物理学 梅德林 电气工程 工程类 政治学 法学
作者
Curtis P. Langlotz
出处
期刊:Radiology [Radiological Society of North America]
卷期号:309 (1) 被引量:12
标识
DOI:10.1148/radiol.231114
摘要

HomeRadiologyVol. 309, No. 1 PreviousNext Reviews and CommentaryEditorial–Centennial ContentThe Future of AI and Informatics in Radiology: 10 PredictionsCurtis P. Langlotz Curtis P. Langlotz Author AffiliationsFrom the Departments of Radiology, Medicine, and Biomedical Data Science, Stanford University School of Medicine, 300 Pasteur Dr, Stanford, CA 94305.Address correspondence to the author (email: [email protected]).Curtis P. Langlotz Published Online:Oct 24 2023https://doi.org/10.1148/radiol.231114MoreSectionsFull textPDF ToolsAdd to favoritesCiteTrack CitationsPermissionsReprints ShareShare onFacebookXLinked In References1. Schwartz WB. Medicine and the computer. The promise and problems of change. N Engl J Med 1970;283(23):1257–1264. Crossref, Medline, Google Scholar2. Center for Devices and Radiological Health. Artificial Intelligence and Machine Learning (AI/ML)-Enabled Medical Devices. 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Center for Artificial Intelligence in Medicine & Imaging. https://aimi.stanford.edu/shared-datasets. Accessed April 15, 2023. Google Scholar45. Chen IY, Pierson E, Rose S, Joshi S, Ferryman K, Ghassemi M. Ethical machine learning in healthcare. Annu Rev Biomed Data Sci 2021;4(1):123–144. Crossref, Medline, Google Scholar46. Recht MP, Dewey M, Dreyer K, et al. Integrating artificial intelligence into the clinical practice of radiology: challenges and recommendations. Eur Radiol 2020;30(6):3576–3584. Crossref, Medline, Google ScholarArticle HistoryReceived: Apr 29 2023Revision requested: May 12 2023Revision received: May 16 2023Accepted: May 22 2023Published online: Oct 24 2023 FiguresReferencesRelatedDetailsCited ByInvited Commentary: The Double-edged Sword of Bias in Medical Imaging Artificial IntelligencePouria Rouzrokh, Bradley J. Erickson, 18 April 2024 | RadioGraphics, Vol. 44, No. 5Human-AI Symbiosis: A Path Forward to Improve Chest Radiography and the Role of Radiologists in Patient CareWarren B. Gefter, Mathias Prokop, Joon Beom Seo, Suhail Raoof, Curtis P. Langlotz, Hiroto Hatabu, 23 January 2024 | Radiology, Vol. 310, No. 1Editor's Note: 2023—The Year in Review for RadiologyLinda Moy, 30 January 2024 | Radiology, Vol. 310, No. 1Development and optimization of AI algorithms for wrist fracture detection in children using a freely available datasetTristanTill, SebastianTschauner, GeorgSinger, KlausLichtenegger, HolgerTill21 December 2023 | Frontiers in Pediatrics, Vol. 11Accompanying This ArticleFuture of AI and InformaticsJan 30 2024Default Digital Object SeriesRecommended Articles Deep Learning: A Primer for RadiologistsRadioGraphics2017Volume: 37Issue: 7pp. 2113-2131Clinical Validation Is the Key to Adopting AI in Clinical PracticeRadiology: Artificial Intelligence2021Volume: 3Issue: 4Current Applications and Future Impact of Machine Learning in RadiologyRadiology2018Volume: 288Issue: 2pp. 318-328Preparing Medical Imaging Data for Machine LearningRadiology2020Volume: 295Issue: 1pp. 4-15Machine Learning Applied to Alzheimer DiseaseRadiology2016Volume: 281Issue: 3pp. 665-668See More RSNA Education Exhibits Why AI Misses Small Organs and How to Improve Their Recognition PerformancesDigital Posters2020Outsmarting AI: What Role Can The Radiologist Play In The Making And Deployment Of Artificial Intelligence ApplicationsDigital Posters2021Uncertainty Estimation in Auto-Segmentation and Image Reconstruction TasksDigital Posters2022 RSNA Case Collection Ischemic stroke in moyamoya diseaseRSNA Case Collection2020Intermittent Port Malfunction RSNA Case Collection2021Fahr's syndromeRSNA Case Collection2021 Vol. 309, No. 1 PodcastMetrics Altmetric Score PDF download
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