Diagnosis of Parkinson's disease using evolutionary algorithms

Created by W.Langdon from gp-bibliography.bib Revision:1.8120

@Article{Smith:2007:GPEM,

• author = "Stephen L. Smith and Patrick Gaughan and David M. Halliday and Quan Ju and Nabil M. Aly and Jeremy R. Playfer",
• title = "Diagnosis of Parkinson's disease using evolutionary algorithms",
• journal = "Genetic Programming and Evolvable Machines",
• year = "2007",
• volume = "8",
• number = "4",
• pages = "433--447",
• month = dec,
• note = "special issue on medical applications of Genetic and Evolutionary Computation",
• keywords = "genetic algorithms, genetic programming, Parkinson's disease, Evolutionary algorithms, Cartesian genetic programming",
• ISSN = "1389-2576",
• DOI = "doi:10.1007/s10710-007-9043-9",
• abstract = "This paper describes the novel application of an evolutionary algorithm to discriminate Parkinson's patients from age-matched controls in their response to simple figure-copying tasks. The reliable diagnosis of Parkinson's disease is notoriously difficult to achieve with misdiagnosis reported to be as high as 25percent of cases. The approach described in this paper aims to distinguish between the velocity profiles of pen movements of patients and controls to identify distinguishing artifacts that may be indicative of the Parkinson's symptom bradykinesia. Results are presented for 12 patients with Parkinson's disease and 10 age-match controls. An algorithm was evolved using half the patient and age-matched control responses, which was then successfully used to correctly classify the remaining responses. A more rigorous leave one out strategy was also applied to the test data with encouraging results.",
• notes = "Wacom digitising tablet, CGP",

}

Genetic Programming entries for Stephen L Smith Patrick Gaughan David M Halliday Quan Ju Nabil M Aly Jeremy R Playfer

Citations