Exploring diagnostic models of Parkinson's disease with multi-objective regression

摘要: Parkinson's disease is a progressive neurodegenerative disorder. The biggest risk factor for developing age and so prevalence increasing in countries where the average of population rising. Cognitive problems are common identifying those with condition who most at such issues an important area research. In this work, we explore potential using objective, automated methods based around simple figure copying exercise administered on graphics tablet to people disease. particular, use multi-objective evolutionary algorithm space regression models, each model represents combination features extracted from patient's digitised drawing. objectives accurately predict clinical measures motor cognitive deficit. Our results show that both these can be predicted, degree, certain sub-sets particularly relevant case.