Using GIS to Profile Health-Care Costs of VA Quality-Enhancement Research Initiative Diseases
Journal of Medical Systems
GIS-EpiLink: A Spatial Search Tool for Linking Environmental and Health Data
Journal of Medical Systems
Data mining and visualization for decision support and modeling of public health-care resources
Journal of Biomedical Informatics
Advances in Fuzzy Systems - Special issue on Fuzzy Methods and Approximate Reasoning in Geographical Information Systems
Hotspots detection in spatial analysis via the extended gustafson-kessel algorithm
Advances in Fuzzy Systems - Special issue on Fuzzy Methods and Approximate Reasoning in Geographical Information Systems
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This study used data mining techniques to investigate disease forms in various administrative areas and to analyze the differences among various administrative areas in order to further draw up a disease distribution map. It is hoped that may help formulate future public health strategies and to allocate medical resources more appropriately. The major disease forms for residents under the age of 60 were hypertension, hyperglycemia and hyperlipidemia. In regard to the neighboring areas, three neighboring areas, A1, A3, and B9, shared the same disease problems with A4, A5, and B3, while two mountain-area cities, B7 and C10, experienced higher instances of liver function impairment. In terms of the clustering phenomenon among municipally graded administrative areas, the major health problems in Grade A cities were hypertension, hyperglycemia, and hyperlipidemia. The health problems such as liver function impairment and renal dysfunction were more frequently observed in Grade B and Grade C cities.