Transformer Unlocks the Gateway to Advanced Research: Predicting Diseases on Chest Radiographs Using Multimodal Data

HomeRadiologyVol. 310, No. 2 PreviousNext CommunicationsLetters to the EditorTransformer Unlocks the Gateway to Advanced Research: Predicting Diseases on Chest Radiographs Using Multimodal DataKengo Takahashi* , Takuma Usuzaki†, Ryusei Inamori*Kengo Takahashi* , Takuma Usuzaki†, Ryusei Inamori*Author Affiliations* Tohoku University Graduate School of Medicine, 2-1 Seiryo-machi, Aoba-ku, Sendai, Miyagi, 980-8573, Miyagi, Japan† Department of Diagnostic Radiology, Tohoku University Hospital, Miyagi, Japanemail: [email protected]Kengo Takahashi* Takuma Usuzaki†Ryusei Inamori*Published Online:Feb 13 2024https://doi.org/10.1148/radiol.232760MoreSectionsFull textPDF ToolsAdd to favoritesCiteTrack CitationsPermissionsReprints ShareShare onFacebookXLinked In References1. Khader F, Müller-Franzes G, Wang T, et al. Multimodal Deep Learning for Integrating Chest Radiographs and Clinical Parameters: A Case for Transformers. Radiology 2023;309(1):e230806. Link, Google Scholar2. Glocker B, Jones C, Roschewitz M, Winzeck S. Risk of Bias in Chest Radiography Deep Learning Foundation Models. Radiol Artif Intell 2023;5(6):e230060. Link, Google Scholar3. Gichoya JW, Banerjee I, Bhimireddy AR, et al. AI recognition of patient race in medical imaging: a modelling study. Lancet Digit Health 2022;4(6):e406–e414. Crossref, Medline, Google Scholar4. Acosta JN, Falcone GJ, Rajpurkar P, Topol EJ. Multimodal biomedical AI. Nat Med 2022;28(9):1773–1784. Crossref, Medline, Google Scholar5. Gil IS, Dong L. Real World Large Scale Recommendation Systems Reproducibility and Smooth Activations. arXiv 2202.06499 [preprint] https://arxiv.org/abs/2202.06499. Published February 14, 2022. Accessed October 1, 2023. Google ScholarArticle HistoryPublished online: Feb 13 2024 FiguresReferencesRelatedDetailsRecommended Articles Combining Initial Radiographs and Clinical Variables Improves Deep Learning Prognostication in Patients with COVID-19 from the Emergency DepartmentRadiology: Artificial Intelligence2020Volume: 3Issue: 2Fully Automated and Standardized Segmentation of Adipose Tissue Compartments via Deep Learning in 3D Whole-Body MRI of Epidemiologic Cohort StudiesRadiology: Artificial Intelligence2020Volume: 2Issue: 6Clinical Performance of Current-Generation AI Tools for Chest RadiographsRadiology2023Volume: 308Issue: 3Deep Learning at Chest Radiography: Automated Classification of Pulmonary Tuberculosis by Using Convolutional Neural NetworksRadiology2017Volume: 284Issue: 2pp. 574-582Mitigating Bias in Radiology Machine Learning: 3. Performance MetricsRadiology: Artificial Intelligence2022Volume: 4Issue: 5See More RSNA Education Exhibits Uncertainty Estimation in Auto-Segmentation and Image Reconstruction TasksDigital Posters2022When Numbers Lie: Pearls And Pitfalls To Avoid In Hounsfield Unit InterpretationDigital Posters2021Artificial Intelligence Applications in Breast Imaging and Challenges for Digital Breast TomosynthesisDigital Posters2020 RSNA Case Collection Pancreatic lymphomaRSNA Case Collection2020Dermatofibrosarcoma ProtuberansRSNA Case Collection2021LymphangioleiomyomatosisRSNA Case Collection2021 Vol. 310, No. 2 Metrics Altmetric Score PDF download