Lazy learning methods for quality of life assessment in people with intellectual disabilities

Eva Armengol*, Pilar Dellunde, Carlo Ratto

*Corresponding author for this work

Research output: Chapter in BookChapterResearchpeer-review

Abstract

In this paper we present a preliminary work applying machine learning techniques to the assessment of quality of life (QOL). In 2008 the Government of Catalonia introduced the GENCAT scale, a QOL questionnaire for dependent people users of the social and human services of Catalonia. Using data from a QOL research of 50 people with intellectual disabilities and/or mental illness of the Taller Jeroni de Moragas, we have applied a lazy learning method to discover relations between the different dimensions considered in the GENCAT scale. Our goal is to provide a basis to refine the model of QOL in a way that could support general intervention programs and a better understanding of the necessities of dependent people. This study is an interdisciplinary research of computer scientists, psychologists and human service practitioners.

Original languageEnglish
Title of host publicationArtificial Intelligence Research and Development - Proceedings of the 14th International Conference of the Catalan Association for Artificial Intelligence
PublisherIOS Press
Pages41-50
Number of pages10
ISBN (Print)9781607508410
DOIs
Publication statusPublished - 2011

Publication series

NameFrontiers in Artificial Intelligence and Applications
Volume232
ISSN (Print)0922-6389

Keywords

  • GENCAT scale
  • Lazy learning methods
  • Machine Learning
  • Psycological applications
  • Quality of life assessment

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