Prescription Prediction towards Computer-Assisted Diagnosis for Kampo Medicine

Xiaoyu Mi, Hiroshi Ikeda, Fumihiko Nakazawa, Hidetoshi Matsuoka, Erika Kataoka, Satoshi Hamaya, Tatsuo Tanaka, Hiroshi Odaguchi, Tatsuya Ishige, Yuichi Ito, Akino Wakasugi, Tadaaki Kawanabe, Mariko Sekine, Toshihiko Hanawa, Shinichi Yamaguchi

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Citations (Scopus)

Abstract

This paper focuses on the attempt to formulate the prescription prediction logic based on the medical data analysis towards the future computer-assisted-diagnosis for Kampo medicine. We constructed and evaluated prediction models for some frequently-used prescriptions using six kinds of machine learning algorithms including artificial neural network, multinomial logit, random forest, support vector machine, k-nearest neighbor, and decision tree. The possibility of prescription prediction and the necessary amount of data required for robust prediction are clarified.

Original languageEnglish
Title of host publicationProceedings - 2015 International Conference on Computer Application Technologies, CCATS 2015
EditorsAntoine Bossard, Satoshi Takahashi, Yohei Shiraki, Toshiyuki Tanaka
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages126-131
Number of pages6
ISBN (Electronic)9781467382113
DOIs
Publication statusPublished - 2016 Jan 4
Event1st International Conference on Computer Application Technologies, CCATS 2015 - Matsue, Japan
Duration: 2015 Aug 312015 Sept 2

Publication series

NameProceedings - 2015 International Conference on Computer Application Technologies, CCATS 2015

Other

Other1st International Conference on Computer Application Technologies, CCATS 2015
Country/TerritoryJapan
CityMatsue
Period15/8/3115/9/2

Keywords

  • Kampo medicine
  • evid
  • holistic
  • induction
  • knowledge discovery
  • machinery learning
  • medical data
  • objectification
  • prescription prediction
  • prescription-syndrome correspondence
  • robust prediction
  • statistical analysis
  • tacit knowledge
  • traditional medicine

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Computer Science Applications

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