Synthetic Data-Driven Approaches for Chinese Medical Abstract Sentence Classification: Computational Study.

Journal: JMIR formative research
PMID: 40106267

Abstract

BACKGROUND: Medical abstract sentence classification is crucial for enhancing medical database searches, literature reviews, and generating new abstracts. However, Chinese medical abstract classification research is hindered by a lack of suitable datasets. Given the vastness of Chinese medical literature and the unique value of traditional Chinese medicine, precise classification of these abstracts is vital for advancing global medical research.

Authors

  • Jiajia Li
    Shanghai Artificial Intelligence Research Institute Co., Ltd, Shanghai, China.
  • Zikai Wang
    Shanghai Artificial Intelligence Research Institute Co., Ltd, Shanghai, China.
  • Longxuan Yu
    University of California San Diego, San Diego, CA, United States.
  • Hui Liu
    Institute of Urology and Nephrology, The First Affiliated Hospital of Guangxi Medical University, Nanning, China.
  • Haitao Song
    Shanghai Artificial Intelligence Research Institute Co., Ltd, Shanghai, China.

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