Scholarly Works per year
Scholarly Works per year
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 |
Research output
- 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
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