|
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 |