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Cancer Research Trends in Traditional Korean Medical Journals since 2000 - Topic Modeling Using Latent Dirichlet Allocation and Keyword Network Analysis

2000년 이후 국내 한의학 암 관련 연구 동향 분석 - Latent Dirichlet Allocation 기반 토픽 모델링 및 연관어 네트워크 분석

  • Kyeore, Bae (National Agency for Development of Innovative Technologies in Korean Medicine, National Institute for Korean Medicine Development (NIKOM))
  • 배겨레 (한국한의약진흥원 한의약혁신기술개발사업단)
  • Received : 2022.10.14
  • Accepted : 2022.12.22
  • Published : 2022.12.30

Abstract

Objectives: The aim of this study is to analyze cancer research trends in traditional Korean medical journals indexed in the Korea Citation Index since 2000. Methods: Cancer research papers published in traditional Korean medical journals were searched in databases from inception to October 2022. The numbers of publications by journal and by year were descriptively assessed. After natural language processing, topic modeling (based on Latent Dirichlet allocation) and keyword network analysis were conducted. Results: This research trend analysis involved 1,265 papers. Six topics were identified by topic modeling: case reports on symptom management, literature reviews, experiments on apoptosis, herbal extract treatments of breast carcinoma cell lines, anti-proliferative effects of herbal extracts, and anti-tumor effects. Keyword network analysis found that the effects of herbal medicine were assessed in clinical and experimental studies, while acupuncture was mainly mentioned in clinical reports. Conclusions: Cancer research papers in traditional Korean medical journals have contributed to evidence-based medicine. Further experimental studies are needed to elucidate the effects of on different hallmarks of cancer. Rigorous clinical studies are needed to support clinical guidelines.

Keywords

Acknowledgement

본 연구는 보건복지부의 재원으로 한국보건산업진흥원의 보건의료기술연구개발사업 지원에 의하여 이루어진 것입니다(과제고유번호: HI20C0867).

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