A three-stage hybrid clustering system for diagnosing children with primary headache disorder. (4th March 2022)

• Record Type: Journal Article
• Authors: Simić, Svetlana; Sakač, Slađana; Banković, Zorana; Villar, José R; Calvo-Rolle, José Luis; Simić, Svetislav D; Simić, Dragan
• Is Part Of: Logic journal of the IGPL. Volume 31:Number 2(2023)
• Page Start: 300
• Page End: 313
• Publication Date: 2022-03-04
• Subjects: diagnosis -- Davies–Bouldin index -- Calinski–Harabasz index -- fuzzy c-means -- analytic hierarchy process -- attribute selection -- headache; Logic, Symbolic and mathematical -- Periodicals; 511.3
• DOI: 10.1093/jigpal/jzac020
• Languages: English
• ISSNs: 1367-0751

Abstract

Abstract: Headache disorders can be considered as the predominant neurological condition. In the field of neurological diseases, migraine was estimated to cost a total of €27 billion per year for the loss through reduced work productivity in the European Community. 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 hybrid clustering system combining analytic hierarchy process and weighted fuzzy c-means clustering method for diagnosing children with primary headache disorder. The proposed three-stage hybrid diagnosing system is tested on data set collected from hospitalized children in the Clinical Centre of Vojvodina, Novi Sad, Serbia.