This paper is in the following e-collection/theme issue:

Theme Issue 2020:National NLP Clinical Challenges/Open Health Natural Language Processing 2019 Challenge Selected Papers (17) Natural Language Processing (692)

Published on in Vol 9, No 1 (2021): January

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/23086, first published .
ALBERT-Based Self-Ensemble Model With Semisupervised Learning and Data Augmentation for Clinical Semantic Textual Similarity Calculation: Algorithm Validation Study

ALBERT-Based Self-Ensemble Model With Semisupervised Learning and Data Augmentation for Clinical Semantic Textual Similarity Calculation: Algorithm Validation Study

ALBERT-Based Self-Ensemble Model With Semisupervised Learning and Data Augmentation for Clinical Semantic Textual Similarity Calculation: Algorithm Validation Study

Authors of this article:

Junyi Li1 Author Orcid Image ;   Xuejie Zhang1 Author Orcid Image ;   Xiaobing Zhou1 Author Orcid Image
Article Authors Cited by (3) Tweetations (3) Metrics

Junyi Li   1 , ME ;   Xuejie Zhang   1 , PhD ;   Xiaobing Zhou   1 , PhD

1 School of Information Science and Engineering, Yunnan University, Kunming, China

Corresponding Author:

  • Xiaobing Zhou, PhD
  • School of Information Science and Engineering
  • Yunnan University
  • East Outer Ring Road
  • Chenggong District, Kunming
  • Kunming, 650091
  • China
  • Phone: 86 87165031748
  • Email: zhouxb@ynu.edu.cn