Article,
Diagnosis of Parkinson's disease using evolutionary algorithms
Genetic Programming and Evolvable Machines, 8 (4): 433--447 (December 2007)special issue on medical applications of Genetic and Evolutionary Computation.
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.
