Title :
Implicit Context Representation Cartesian Genetic Programming for the assessment of visuo-spatial ability
Author :
Smith, Stephen L. ; Lones, Michael A.
Author_Institution :
Dept. of Electron., Univ. of York, York
Abstract :
In this paper, a revised form of implicit context representation Cartesian genetic programming is used in the development of a diagnostic tool for the assessment of patients with neurological dysfunction such as Alzheimer´s disease. Specifically, visuo-spatial ability is assessed by analysing subjects´ digitised responses to a simple figure copying task using a conventional test environment. The algorithm was trained to distinguish between classes of visuo-spatial ability based on responses to the figure copying test by 7-11 year old children in which visuo-spatial ability is at varying stages of maturity. Results from receiver operating characteristic (ROC) analysis are presented for the training and subsequent testing of the algorithm and demonstrate this technique has the potential to form the basis of an objective assessment of visuo-spatial ability.
Keywords :
diseases; genetic algorithms; neurophysiology; patient diagnosis; Alzheimer´s disease; Cartesian genetic programming; diagnostic tool; implicit context representation; neurological dysfunction; patients assessment; receiver operating characteristic analysis; visuo-spatial ability assessment; Algorithm design and analysis; Alzheimer´s disease; Brain; Cost accounting; Genetic programming; Intelligent systems; Medical treatment; Parkinson´s disease; Testing; Time measurement;
Conference_Titel :
Evolutionary Computation, 2009. CEC '09. IEEE Congress on
Conference_Location :
Trondheim
Print_ISBN :
978-1-4244-2958-5
Electronic_ISBN :
978-1-4244-2959-2
DOI :
10.1109/CEC.2009.4983065