A Hybrid Bio-inspired Clustering Approach for Diagnosing Children with Primary Headache Disorder

摘要

Half of the general population experiences a headache during any given year. Medical data and information in turn provide knowledge based on which physicians make scientific decisions for diagnosis and treatments. It is, therefore, very useful to create diagnostic tools to help physicians make better decisions. This paper is focused on a new approach based on a model for combining fuzzy partition method and bat clustering algorithm for diagnosing children with primary headache disorder. The proposed hybrid system is tested on data set collected from hospitalized children in Clinical Centre of Vojvodina, Novi Sad, Serbia.