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

Development and Evaluation of Research Methods, Instruments and Tools (744) Natural Language Processing (917) Artificial Intelligence (2129) Machine Learning (2076) Computer-Aided Diagnosis (251) Tools, Programs and Algorithms (376) Complementary and Alternative Medicine (94) Ontologies, Classifications, and Coding (324)

Published on in Vol 9 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/70602, first published .
Identification of Syndrome Types in Patients With Pancreatic Cancer From Free Text in Electronic Medical Records: Model Development and Validation

Identification of Syndrome Types in Patients With Pancreatic Cancer From Free Text in Electronic Medical Records: Model Development and Validation

Identification of Syndrome Types in Patients With Pancreatic Cancer From Free Text in Electronic Medical Records: Model Development and Validation

Authors of this article:

He Ba1, 2 Author Orcid Image ;   Haojie Du3, 4 Author Orcid Image ;   Chienshan Cheng2, 5 Author Orcid Image ;   Yuan Zhang2, 5 Author Orcid Image ;   Linjie Ruan2, 5 Author Orcid Image ;   Zhen Chen2, 5 Author Orcid Image
Article Authors Cited by Tweetations (3) Metrics

He Ba   1, 2 * , PhD ;   Haojie Du   3, 4 * , MEng ;   Chienshan Cheng   2, 5 , MD ;   Yuan Zhang   2, 5 , MD ;   Linjie Ruan   2, 5 , MD ;   Zhen Chen   2, 5 , Prof Dr Med

1 Qingdao Institute, Department of Integrative Oncology, Fudan University Shanghai Cancer Center, Qingdao, China

2 Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China

3 Key Laboratory of Surface & Interface Science of Polymer Materials of Zhejiang Province, School of Chemistry and Chemical Engineering, Zhejiang Sci-Tech University, Hangzhou, China

4 Shengzhou Innovation Research Institute of Zhejiang Sci-Tech University, Shengzhou, China

5 Department of Integrative Oncology, Fudan University Shanghai Cancer Center, Shanghai, China

*these authors contributed equally

Corresponding Author:

  • Zhen Chen, Prof Dr Med
  • Department of Integrative Oncology
  • Fudan University Shanghai Cancer Center
  • No. 270 Dongan Rd., Xuhui district
  • Shanghai
  • China
  • Phone: 86 13311965818
  • Email: zchenzl@fudan.edu.cn