Observatorio de I+D+i UPM

Memorias de investigación
Communications at congresses:
Restating clinical impression of severity index for Parkinson's disease using just non-motor criteria
Year:2012
Research Areas
  • Artificial intelligence
Information
Abstract
Clinical impression of severity index for Parkinson?s disease (CISI-PD) is an index that evaluates complex aspects of the patients cognitive state. Since this is a continuous value, a categorization policy is proposed by solving an optimization problem. Using this encoding, different comparisons between CISI-PD and other non-motor indexes or items are addressed using wrapper item subset selection and estimation of distribution algorithms. Results show how some of the non-motor items are very relevant, achieving good classification performances when used to predict the CISI-PD severity index.
International
Si
Congress
25th European Conference on Operational Research
960
Place
Vilnius (Lituania)
Reviewers
No
ISBN/ISSN
Start Date
08/07/2012
End Date
11/07/2012
From page
231
To page
232
Proceedings of the 25th European Conference on Operational Research
Participants
  • Autor: Ruben Armañanzas Arnedillo (UPM)
  • Autor: Pablo Martínez-Martín (Fundación CIEN)
  • Autor: Maria Concepcion Bielza Lozoya (UPM)
  • Autor: Pedro Maria Larrañaga Mugica (UPM)
Research Group, Departaments and Institutes related
  • Creador: Grupo de Investigación: COMPUTATIONAL INTELLIGENCE GROUP
  • Departamento: Inteligencia Artificial
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