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Descripción
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| 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. | |
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Internacional
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Si |
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Nombre congreso
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25th European Conference on Operational Research |
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Tipo de participación
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960 |
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Lugar del congreso
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Vilnius (Lituania) |
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Revisores
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No |
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ISBN o ISSN
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DOI
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Fecha inicio congreso
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08/07/2012 |
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Fecha fin congreso
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11/07/2012 |
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Desde la página
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231 |
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Hasta la página
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232 |
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Título de las actas
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Proceedings of the 25th European Conference on Operational Research |