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

Vincent M. D’Anniballe (Creator)
Fakrul I. Tushar (Creator)
Khrystyna Faryna (Creator)
Songyue Han (Creator)
MacIej A. Mazurowski (Creator)
Geoffrey D Rubin (Creator)
Joseph Y. Lo (Creator)

Medical Imaging

Dataset

Description

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)...

Date made available	2022
Publisher	figshare

DOI
10.6084/m9.figshare.c.5951163

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Creative Commons Attribution 4.0 International

1 Article

Multi-label annotation of text reports from computed tomography of the chest, abdomen, and pelvis using deep learning
D’Anniballe, V. M., Tushar, F. I., Faryna, K., Han, S., Mazurowski, M. A., Rubin, G. D. & Lo, J. Y., Dec 2022, In: BMC Medical Informatics and Decision Making. 22, 1, 102.
Research output: Contribution to journal › Article › peer-review

Open Access
9 Scopus citations

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

Description

DOI

Access Dataset

Research output

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

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