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Clinical Chinese named entity recogn...

Guo, Shuli.

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Clinical Chinese named entity recognition in natural language processing

Record Type:	Electronic resources : Monograph/item
Title/Author:	Clinical Chinese named entity recognition in natural language processing/ by Shuli Guo, Lina Han, Wentao Yang.
Author:	Guo, Shuli.
other author:	Han, Lina.
Published:	Singapore :Springer Nature Singapore : : 2023.,
Description:	1 online resource (xx, 90 p.) :ill., digital ;24 cm.
[NT 15003449]:	Introduction -- Theoretical Basis -- Related Existed Models -- Medical Named Entity Recognition Models with the Attention Distraction Mechanism -- Transformer Entity Automatic Extraction Models in Multi-Layer Soft Location Matching Format -- Medical Named Entity Recognition Modelling based on Remote Monitoring and Denoising.
Contained By:	Springer Nature eBook
Subject:	Natural language processing (Computer science) -
Online resource:	https://doi.org/10.1007/978-981-99-2665-7
ISBN:	9789819926657

Clinical Chinese named entity recognition in natural language processing
Guo, Shuli.

Clinical Chinese named entity recognition in natural language processing[electronic resource] /by Shuli Guo, Lina Han, Wentao Yang. - Singapore :Springer Nature Singapore :2023. - 1 online resource (xx, 90 p.) :ill., digital ;24 cm.

Introduction -- Theoretical Basis -- Related Existed Models -- Medical Named Entity Recognition Models with the Attention Distraction Mechanism -- Transformer Entity Automatic Extraction Models in Multi-Layer Soft Location Matching Format -- Medical Named Entity Recognition Modelling based on Remote Monitoring and Denoising.

This book introduces how to enhance the context capture ability of the model, improve the position information perception ability of the pretrained models, and identify and denoise the unlabeled entities. The Chinese medical named entity recognition is an important branch of the intelligent medicine, which is beneficial to mine the information hidden in medical texts and provide the medical entity information for clinical medical decision-making and medical classification. Researchers, engineers and post-graduate students in the fields of medicine management and software engineering.

ISBN: 9789819926657

Standard No.: 10.1007/978-981-99-2665-7doiSubjects--Topical Terms:

565309
Natural language processing (Computer science)

LC Class. No.: QP76.9.N38

Dewey Class. No.: 006.35

Clinical Chinese named entity recognition in natural language processing
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245 1 0 $a Clinical Chinese named entity recognition in natural language processing $h [electronic resource] / $c by Shuli Guo, Lina Han, Wentao Yang.
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300 $a 1 online resource (xx, 90 p.) : $b ill., digital ; $c 24 cm.
505 0 $a Introduction -- Theoretical Basis -- Related Existed Models -- Medical Named Entity Recognition Models with the Attention Distraction Mechanism -- Transformer Entity Automatic Extraction Models in Multi-Layer Soft Location Matching Format -- Medical Named Entity Recognition Modelling based on Remote Monitoring and Denoising.
520 $a This book introduces how to enhance the context capture ability of the model, improve the position information perception ability of the pretrained models, and identify and denoise the unlabeled entities. The Chinese medical named entity recognition is an important branch of the intelligent medicine, which is beneficial to mine the information hidden in medical texts and provide the medical entity information for clinical medical decision-making and medical classification. Researchers, engineers and post-graduate students in the fields of medicine management and software engineering.
650 0 $a Natural language processing (Computer science) $3 565309
650 0 $a Medical informatics $z China. $3 3634528
650 0 $a Text data mining $z China. $3 3634529
650 1 4 $a Machine Learning. $3 3382522
650 2 4 $a Computational Linguistics. $3 893900
650 2 4 $a Clinical Research. $3 3531315
650 2 4 $a Computer Imaging, Vision, Pattern Recognition and Graphics. $3 890871
700 1 $a Han, Lina. $3 3308622
700 1 $a Yang, Wentao. $3 3634527
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856 4 0 $u https://doi.org/10.1007/978-981-99-2665-7
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