PASCAL: a pseudo cascade learning framework for breast cancer treatment entity normalization in Chinese clinical text

PASCAL: a pseudo cascade learning framework for breast cancer treatment entity normalization in Chinese clinical text

Abstract Backgrounds Knowledge discovery from breast cancer treatment records has promoted downstream clinical studies such as careflow mining and therapy analysis. However, the clinical treatment text from electronic health data might be recorded by different doctors under their hospital guidelines...

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Bibliographic Details
Main Authors: Yang An, Jianlin Wang, Liang Zhang, Hanyu Zhao, Zhan Gao, Haitao Huang, Zhenguang Du, Zengtao Jiao, Jun Yan, Xiaopeng Wei, Bo Jin
Format: Article
Language:English
Published: BMC 2020-08-01
Series:BMC Medical Informatics and Decision Making
Subjects:
Breast cancer
Cascade learning
Treatment entity normalization
Chinese clinical text mining
Online Access:http://link.springer.com/article/10.1186/s12911-020-01216-9

Internet

http://link.springer.com/article/10.1186/s12911-020-01216-9

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