Knowledge discovery on functional disabilities using clustering based on rules on WHO-DAS II

K. Gibert, R. Annicchiarico, J. Rodas, U. Cortes, U. Nocentini, C. Caltagirone

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

Abstract

Senior citizens represent a fast growing proportion of the population in Europe and other developed areas. This increases the proportion of persons with disability and reduced quality of life. The concept of disability itself is not always precise and quantifiable. To improve agreement on the concept of disability, the World Health Organization (WHO) developed a clinical test $WHO Disability Assessment Schedule (WHO-DAS II) - that is understood to include physical, mental, and social well-being, as a generic measure of functioning. From the medical point of view, the purpose of this work is to extract knowledge on the performance of WHO-DAS II on the basis of a sample of neurological patients from an Italian hospital. This knowledge discovery problem has been faced using clustering based on rules, a technique stablished on 1994 by Gibert which combines some inductive learning (from AI) methods with statistics to extract knowledge on ill-structured domains (complex domains where consensus is not achieved). The results of applying this technique to the WHO-DAS II results is presented.

Original languageEnglish
Title of host publicationProceedings of the International Conference on Information Technology Interfaces, ITI
PublisherUniversity of Zagreb
Pages181-186
Number of pages6
ISBN (Print)9539676967, 9789539676962
DOIs
Publication statusPublished - 2003
Event25th International Conference on Information Technology Interfaces, ITI 2003 - Cavtat, Croatia
Duration: Jun 16 2003Jun 19 2003

Other

Other25th International Conference on Information Technology Interfaces, ITI 2003
CountryCroatia
CityCavtat
Period6/16/036/19/03

Keywords

  • Assessment
  • Clustering based on rules
  • Disability
  • Knowledge based applications in medicine
  • Knowledge Discovery
  • Neurological disease
  • scale (clinical test)

ASJC Scopus subject areas

  • Computer Science(all)

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