Therapeutic category improvement method based on the words appearing in effect-efficacy description

Hirotsugu Ishida, Keita Nabeta, Masaomi Kimura, Michiko Ohkura, Fumito Tsuchiya

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

Abstract

Medical drugs have various efficacies, and are classified focusing on their purpose of use. In Japan, the Ministry of Internal Affairs and Communications gives Japan standard commodity classification (JSCC) numbers to drugs. Therapeutic category numbers are decided based on three digit numbers after the head digits "87". Although the current JSCC numbers are determined based on the revised document "Japan standard commodity classification" compiled in 1990, they have not been revised for 20 years. As a result, when drugs are categorized based on this categorizing system, some drugs are not applicable to any category. As the result, the drugs have been categorized as "other categories" such as "drug for other allergy" or "drug for other cardiovascular disease." The number of such drugs is increasing. However, since it is conceivable that drugs having similar efficacy are often included in other categories, it is necessary that such drugs are classified independently from the "other categories." Therefore, in this study, we analyzed drugs information categorized as "drugs for other cardiovascular disease," and proposed a method of classifying these drugs by using clustering.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Pages174-181
Number of pages8
Volume6764 LNCS
EditionPART 4
DOIs
Publication statusPublished - 2011
Event14th International Conference on Human-Computer Interaction, HCI International 2011 - Orlando, FL
Duration: 2011 Jul 92011 Jul 14

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 4
Volume6764 LNCS
ISSN (Print)03029743
ISSN (Electronic)16113349

Other

Other14th International Conference on Human-Computer Interaction, HCI International 2011
CityOrlando, FL
Period11/7/911/7/14

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Keywords

  • Clustering
  • Medical Safety
  • Therapeutic Category

ASJC Scopus subject areas

  • Computer Science(all)
  • Theoretical Computer Science

Cite this

Ishida, H., Nabeta, K., Kimura, M., Ohkura, M., & Tsuchiya, F. (2011). Therapeutic category improvement method based on the words appearing in effect-efficacy description. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (PART 4 ed., Vol. 6764 LNCS, pp. 174-181). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 6764 LNCS, No. PART 4). https://doi.org/10.1007/978-3-642-21619-0_23