title: DisArticle: a web server for SVM-based discrimination of articles on traditional medicine.
abstract: BACKGROUND
  Much research has been done in Northeast Asia to show the efficacy of traditional medicine. While MEDLINE contains many biomedical articles including those on traditional medicine, it does not categorize those articles by specific research area. The aim of this study was to provide a method that searches for articles only on traditional medicine in Northeast Asia, including traditional Chinese medicine, from among the articles in MEDLINE.
  
  
  RESULTS
  This research established an SVM-based classifier model to identify articles on traditional medicine. The TAK + HM classifier, trained with the features of title, abstract, keywords, herbal data, and MeSH, has a precision of 0.954 and a recall of 0.902. In particular, the feature of herbal data significantly increased the performance of the classifier. By using the TAK + HM classifier, a total of about 108,000 articles were discriminated as articles on traditional medicine from among all articles in MEDLINE. We also built a web server called DisArticle ( http://informatics.kiom.re.kr/disarticle ), in which users can search for the articles and obtain statistical data.
  
  
  CONCLUSIONS
  Because much evidence-based research on traditional medicine has been published in recent years, it has become necessary to search for articles on traditional medicine exclusively in literature databases. DisArticle can help users to search for and analyze the research trends in traditional medicine.
authors.affiliation: Mibyeong Research Center, Korea Institute of Oriental Medicine, 1672 Yuseong-daero, Yuseong-gu, Daejeon, 34054, Republic of Korea. skkim@kiom.re.kr.
authors.forename: Sang-Kyun
authors.initials: SK
authors.lastname: Kim
authors.affiliation: National Center of Excellence in Software, Chungnam National University, 99 Daehak-ro, Yuseong-gu, Daejeon, 34134, Republic of Korea.
authors.forename: SeJin
authors.initials: S
authors.lastname: Nam
authors.affiliation: Mibyeong Research Center, Korea Institute of Oriental Medicine, 1672 Yuseong-daero, Yuseong-gu, Daejeon, 34054, Republic of Korea.
authors.forename: SangHyun
authors.initials: S
authors.lastname: Kim
mesh_terms: D001208:Asia; D035843:Biomedical Research / Q000145:classification* / Q000706:statistics & numerical data; D016208:Databases, Factual; D004365:Drugs, Chinese Herbal; D019317:Evidence-Based Medicine; D029001:Herbal Medicine; D006801:Humans; D020407:Internet; D016239:MEDLINE / Q000145:classification*; D008516:Medicine, Chinese Traditional; D008519:Medicine, Traditional; D008517:Phytotherapy; D010946:Plants, Medicinal; D011643:Publishing; D060388:Support Vector Machine
chemical_list: D004365:Drugs, Chinese Herbal
keywords: MEDLINE; Northeast Asia; Support vector machine; Traditional medicine; Trend analysis