Proceedings of the 10th annual conference companion on Genetic and evolutionary computation
Hardware Acceleration of an Immune Network Inspired Evolutionary Algorithm for Medical Diagnosis
ICES '08 Proceedings of the 8th international conference on Evolvable Systems: From Biology to Hardware
CEC'09 Proceedings of the Eleventh conference on Congress on Evolutionary Computation
Diagnosis of hypoglycemic episodes using a neural network based rule discovery system
Expert Systems with Applications: An International Journal
Evolving computational dynamical systems to recognise abnormal human motor function
IPCAT'12 Proceedings of the 9th international conference on Information Processing in Cells and Tissues
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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 25% 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.