Relation extraction for colorectal cancer via deep learning with entity-aware feature orthogonal decomposition

Relation extraction is significant for text structuring of colorectal cancer (CRC) pathological reports to facilitate doctors’ disease diagnoses. Although many relation extraction methods have been extensively studied for various natural language processing applications, they cannot be well transfer...

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Veröffentlicht in:	Expert systems with applications Jg. 258; S. 125188
Hauptverfasser:	Luo, Zhihao, Feng, Jianjun, Cai, Nian, Wang, Xiaodan, Liao, Jiacheng, Li, Quanqing, Peng, Fuqiang, Chen, Chuanwen
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Elsevier Ltd 15.12.2024
Schlagworte:	Colorectal cancer Feature orthogonal decomposition Pathological reports Relation extraction Stage-wise cross entropy Two-stream feature extraction Relation extraction Feature orthogonal decomposition Two-stream feature extraction Pathological reports Stage-wise cross entropy Colorectal cancer
ISSN:	0957-4174
Online-Zugang:	Volltext
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