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Character-Based Deep Learning Approaches for Clinical Named Entity Recognition: A Comparative Study Using Chinese EHR Texts

Crossref DOI link: https://doi.org/10.1007/978-3-030-34482-5_28

Published Online: 2019-12-02

Published Print: 2019

Update policy: https://doi.org/10.1007/springer_crossmark_policy

Authors

Wu, Jun http://orcid.org/0000-0002-6628-8911
Shao, Dan-rui http://orcid.org/0000-0002-7895-3405
Guo, Jia-hang http://orcid.org/0000-0002-7864-1153
Cheng, Yao http://orcid.org/0000-0003-4247-6843
Huang, Ge http://orcid.org/0000-0002-5606-2740
License Information

Text and Data Mining valid from 2019-01-01

Text and Data Mining valid from 2019-01-01

Version of Record valid from 2019-01-01
More Information

Chapter History

First Online: 2 December 2019

Conference Information

Conference Acronym: ICSH

Conference Name: International Conference on Smart Health

Conference City: Shenzhen

Conference Country: China

Conference Year: 2019

Conference Start Date: 1 July 2019

Conference End Date: 2 July 2019

Conference Number: 7

Conference ID: icsh2019

Conference URL: http://2019.icshconf.org/

Peer Review Information (provided by the conference organizers)

Type: Double-blind

Conference Management System: Conferency.com

Number of Submissions Sent for Review: 43

Number of Full Papers Accepted: 34

Number of Short Papers Accepted: 34

Acceptance Rate of Full Papers: 79% - The value is computed by the equation "Number of Full Papers Accepted / Number of Submissions Sent for Review * 100" and then rounded to a whole number.

Average Number of Reviews per Paper: 4

Average Number of Papers per Reviewer: 4

External Reviewers Involved: No