Multi-label annotation of text reports from computed tomography of the chest, abdomen, and pelvis using deep learning

Abstract Background There is progress to be made in building artificially intelligent systems to detect abnormalities that are not only accurate but can handle the true breadth of findings that radiologists encounter in body (chest, abdomen, and pelvis) computed tomography (CT). Currently, the major...

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Detalhes bibliográficos
Main Authors: Vincent M. D’Anniballe, Fakrul Islam Tushar, Khrystyna Faryna, Songyue Han, Maciej A. Mazurowski, Geoffrey D. Rubin, Joseph Y. Lo
Formato: Artigo
Idioma:Inglês
Publicado em: BMC 2022-04-01
Colecção:BMC Medical Informatics and Decision Making
Assuntos:
Weak supervision
Report labeling
Attention RNN
Rule-based algorithm
Natural language processing
Computed tomography
Acesso em linha:https://doi.org/10.1186/s12911-022-01843-4
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