Application of density estimation algorithms in analyzing co-morbidities of migraine
Journal
Network Modeling and Analysis in Health Informatics and Bioinformatics
Journal Volume
2
Journal Issue
2
Pages
95-107
Date Issued
2013
Author(s)
Abstract
In this study, we will propose a density estimation based data analysis procedure to investigate the co-morbid associations between migraine and the suspected diseases. The primary objective of this study has aimed to develop a novel analysis procedure that can discover insightful knowledge from large medical databases. The entire analysis procedure consists of two stages. During the first stage, a kernel density estimation algorithm named relaxed variable kernel density estimation (RVKDE) is invoked to identify the samples of interest. Then, in the second stage, a density estimation algorithm based on generalized Gaussian components and named G2DE is invoked to provide a summarized description of the distribution. The results obtained by applying the proposed two-staged procedure to analyze co-morbidities of migraine revealed that the proposed procedure could effectively identify a number of clusters of samples with distinctive characteristics. The results further revealed that the distinctive characteristics of the clusters extracted by the proposed procedure were in conformity with the observations reported in recently published articles. Accordingly, it is conceivable that the proposed analysis procedure can be exploited to provide valuable clues of pathogenesis and facilitate development of proper treatment strategies. ? 2013 The Author(s).
Subjects
Co-morbidity; Density estimation algorithm; Drug treatment; Migraine
SDGs
Other Subjects
amitriptyline; ergotamine; flunarizine; propranolol; topiramate; valproic acid; adult; aged; algorithm; article; cardiovascular disease; comorbidity; controlled study; data analysis; data base; density estimation algorithm; disease classification; endocrine disease; female; gastrointestinal disease; head and neck disease; human; kernel method; liver disease; major clinical study; male; mental disease; metabolic disorder; migraine; musculoskeletal disease; neurologic disease; prescription; priority journal
Type
journal article