Artificial intelligence for thoracic radiology: from research tool to clinical practice
- PMID: 34016606
- DOI: 10.1183/13993003.00625-2021
Artificial intelligence for thoracic radiology: from research tool to clinical practice
Conflict of interest statement
Conflict of Interest: L. Calandriello declares honoraria from Boehringer Ingelheim and Roche. Conflict of interest: S.L.F. Walsh declares a fellowship and honoraria from the National Institute for Health Research; consultancy fees and honoraria from Boehringer Ingelheim, Sanofi-Genzyme, Galapagos, Roche, Bracco, Fluidda, the Open Source Imaging Consortium, Oncoarendi Therapeutics and Medscape; and advisory board membership for Boehringer Ingelheim, Sanofi-Genzyme, Galapagos and Roche.
Comment on
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Development and validation of a deep learning algorithm detecting 10 common abnormalities on chest radiographs.Eur Respir J. 2021 May 20;57(5):2003061. doi: 10.1183/13993003.03061-2020. Print 2021 May. Eur Respir J. 2021. PMID: 33243843 Free PMC article.
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