Leveraging GPT-4 for Post Hoc Transformation of Free-text Radiology Reports into Structured Reporting: A Multilingual Feasibility Study

HomeRadiologyVol. 307, No. 4 PreviousNext Original ResearchComputer ApplicationsLeveraging GPT-4 for Post Hoc Transformation of Free-text Radiology Reports into Structured Reporting: A Multilingual Feasibility StudyLisa C. Adams, Daniel Truhn, Felix Busch, Avan Kader, Stefan M. Niehues, Marcus R. Makowski, Keno K. Bressem Lisa C. Adams, Daniel Truhn, Felix Busch, Avan Kader, Stefan M. Niehues, Marcus R. Makowski, Keno K. Bressem Author AffiliationsFrom the Department of Radiology, Stanford University, Stanford, Calif (L.C.A.); Department of Radiology, University Hospital RWTH Aachen, Aachen, Germany (D.T.); Department of Radiology, Charité–Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Campus Benjamin Franklin, Hindenburgdamm 30, 12203 Berlin, Berlin, Germany (L.C.A., F.B., A.K., S.M.N., K.K.B.); and Department of Diagnostic and Interventional Radiology, Technical University of Munich, Munich, Germany (M.R.M.).Address correspondence to K.K.B. (email: [email protected]).Lisa C. AdamsDaniel TruhnFelix BuschAvan KaderStefan M. NiehuesMarcus R. MakowskiKeno K. Bressem Published Online:Apr 4 2023https://doi.org/10.1148/radiol.230725MoreSectionsFull textPDF ToolsAdd to favoritesCiteTrack CitationsPermissionsReprints ShareShare onFacebookXLinked In AbstractGenerative Pre-trained Transformer 4 automates the transformation of various free-text radiology reports into structured templates with minor effort, overcoming the challenges of implementing structured reporting while improving standardization and data extraction for research.Download as PowerPointReferences1. Larson DB, Towbin AJ, Pryor RM, Donnelly LF. Improving consistency in radiology reporting through the use of department-wide standardized structured reporting. Radiology 2013;267(1):240–250. Link, Google Scholar2. Mamlouk MD, Chang PC, Saket RR. Contextual radiology reporting: a new approach to neuroradiology structured templates. AJNR Am J Neuroradiol 2018;39(8):1406–1414. Medline, Google Scholar3. Hegazi TM, Wu JS. Sample MSK MRI Reports. 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Google ScholarArticle HistoryReceived: Mar 23 2023Revision requested: Mar 28 2023Revision received: Mar 28 2023Accepted: Mar 30 2023Published online: Apr 04 2023 FiguresReferencesRelatedDetailsCited ByWhat we can learn from deep space communication for reproducible bioimaging and data analysisTatianaWoller, Christopher JCawthorne, Romain Raymond AgnesSlootmaekers, Ingrid BarcenaRoig, AlexanderBotzki, SebastianMunck13 December 2023 | Molecular Systems Biology, Vol. 20, No. 1Accuracy of ChatGPT generated diagnosis from patient's medical history and imaging findings in neuroradiology casesDaisukeHoriuchi, HiroyukiTatekawa, TaroShimono, Shannon LWalston, HirotakaTakita, ShuMatsushita, TatsushiOura, YasuhitoMitsuyama, YukioMiki, DaijuUeda23 November 2023 | Neuroradiology, Vol. 66, No. 1Uncover This Tech Term: TransformersAmitGupta, KrithikaRangarajan2024Jan1 | Korean Journal of Radiology, Vol. 25, No. 1Chatbots and Large Language Models in Radiology: A Practical Primer for Clinical and Research ApplicationsRajesh Bhayana, 16 January 2024 | Radiology, Vol. 310, No. 1Extracting structured information from unstructured histopathology reports using generative pre‐trained transformer 4 ( GPT ‐4)DanielTruhn, Chiara MLLoeffler, GustavMüller‐Franzes, SvenNebelung, Katherine JHewitt, SebastianBrandner, Keno KBressem, SebastianFoersch, Jakob NikolasKather14 December 2023 | The Journal of Pathology, Vol. 35Top Publications in Radiology, 2023: Our 100th YearLinda Moy, 12 December 2023 | Radiology, Vol. 309, No. 3Generative AI in Medical Imaging: Applications, Challenges, and EthicsMohamadKoohi-Moghadam, Kyongtae TyBae31 August 2023 | Journal of Medical Systems, Vol. 47, No. 1A pilot study on the efficacy of GPT-4 in providing orthopedic treatment recommendations from MRI reportsDanielTruhn, Christian D.Weber, Benedikt J.Braun, KenoBressem, Jakob N.Kather, ChristianeKuhl, SvenNebelung17 November 2023 | Scientific Reports, Vol. 13, No. 1ESR paper on structured reporting in radiology—update 2023, Daniel Pintodos Santos, ElmarKotter, PeterMildenberger, LuisMartí-Bonmatí23 November 2023 | Insights into Imaging, Vol. 14, No. 1O structured reporting, where art thou?DanielPinto dos Santos, RenatoCuocolo, MerelHuisman27 November 2023 | European Radiology, Vol. 6Structured reporting in radiology enables epidemiological analysis through data mining: urolithiasis as a use caseTobiasJorg, Moritz C.Halfmann, NiklasRölz, RenéMager, DanielPinto dos Santos, ChristophDüber, PeterMildenberger, LukasMüller19 July 2023 | Abdominal Radiology, Vol. 48, No. 11To BERT or not to BERT: advancing non-invasive prediction of tumor biomarkers using transformer-based natural language processing (NLP)Ali S.Tejani22 September 2023 | European Radiology, Vol. 33, No. 11Bridging Language and Stylistic Barriers in IR Standardized Reporting: Enhancing Translation and Structure Using ChatGPT-4FumiSasaki, HiroyukiTatekawa, YasuhitoMitsuyama, KenKageyama, AtsushiJogo, AkiraYamamoto, YukioMiki, DaijuUeda2023Nov1 | Journal of Vascular and Interventional Radiology, Vol. 308International pharmacy students' perceptions towards artificial intelligence in medicine—A multinational, multicentre cross‐sectional studyFelixBusch, LenaHoffmann, DanielTruhn, SubishPalaian, MuaedAlomar, KlevaShpati, Marcus RichardMakowski, Keno KyrillBressem, Lisa ChristineAdams6 October 2023 | British Journal of Clinical PharmacologyFeasibility of Using the Privacy-preserving Large Language Model Vicuna for Labeling Radiology ReportsPritam Mukherjee, Benjamin Hou, Ricardo B. 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