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

Theme issue 2019: Health Natural Language Processing (17) Complementary and Alternative Medicine (18) Natural Language Processing (650) Ontologies, Classifications, and Coding (226) Innovations and Technology in Cancer Care (405) Innovations in Cancer Diagnostic and Decision Support (52) Lung Cancer (30)

Published on in Vol 8, No 6 (2020): June

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/17821, first published .
End-to-End Models to Imitate Traditional Chinese Medicine Syndrome Differentiation in Lung Cancer Diagnosis: Model Development and Validation

End-to-End Models to Imitate Traditional Chinese Medicine Syndrome Differentiation in Lung Cancer Diagnosis: Model Development and Validation

End-to-End Models to Imitate Traditional Chinese Medicine Syndrome Differentiation in Lung Cancer Diagnosis: Model Development and Validation

Authors of this article:

Ziqing Liu1, 2 Author Orcid Image ;   Haiyang He3 Author Orcid Image ;   Shixing Yan3 Author Orcid Image ;   Yong Wang4 Author Orcid Image ;   Tao Yang2 Author Orcid Image ;   Guo-Zheng Li1 Author Orcid Image
Article Authors Cited by (18) Tweetations (1) Metrics

Ziqing Liu   1, 2 * ;   Haiyang He   3 * , MA ;   Shixing Yan   3 , MA ;   Yong Wang   4 , BA ;   Tao Yang   2 , PhD, MD ;   Guo-Zheng Li   1 , PhD

1 Second School of Clinic Medicine, Guangzhou University of Chinese Medicine, Guangzhou, China

2 School of Artifical Intelligence and Information Techology, Nanjing University of Chinese Medicine, Nanjing, China

3 Shanghai Bright AI Co, Ltd, Shanghai, China

4 Shanghai Literature Institute of Traditional Chinese Medicine, Shanghai, China

*these authors contributed equally

Corresponding Author:

  • Tao Yang, PhD, MD
  • School of Artifical Intelligence and Information Techology
  • Nanjing University of Chinese Medicine
  • Nanjing
  • China
  • Phone: 86 13405803341
  • Fax: 86 02585811573
  • Email: taoyang1111@126.com