Automatic text classification of actionable radiology reports of tinnitus patients using bidirectional encoder representations from transformer (BERT) and in-domain pre-training (IDPT)

Automatic text classification of actionable radiology reports of tinnitus patients using bidirectional encoder representations from transformer (BERT) and in-domain pre-training (IDPT)

Abstract Background Given the increasing number of people suffering from tinnitus, the accurate categorization of patients with actionable reports is attractive in assisting clinical decision making. However, this process requires experienced physicians and significant human labor. Natural language...

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Bibliographic Details
Main Authors: Jia Li, Yucong Lin, Pengfei Zhao, Wenjuan Liu, Linkun Cai, Jing Sun, Lei Zhao, Zhenghan Yang, Hong Song, Han Lv, Zhenchang Wang
Format: Article
Language:English
Published: BMC 2022-07-01
Series:BMC Medical Informatics and Decision Making
Subjects:
Artificial intelligence
Natural language processing
Deep learning
Radiology report
Bidirectional encoding representation of transformer
Online Access:https://doi.org/10.1186/s12911-022-01946-y

Internet

https://doi.org/10.1186/s12911-022-01946-y

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