Padrões de Incidência Geográfica da Doença Pulmonar Obstrutiva Crónica e da Asma em Portugal, Maribel Yasmina Santos (superv.), Universidade do Minho, December 2011.
Keywords: chronic obstructive pulmonary disease; shared nearest neighbours; spatial characterization
Abstract: Data Mining algorithms have been used to analyse huge amounts of data and extract useful models or patterns from the analysed data. Those models or patterns can be used to support the decision making process in organisations. In the health domain, and besides the support to the decision process, those algorithms are useful in the analysis and characterization of several diseases. This work presents the particular case of the use of clustering algorithms to support health care specialists in the analysis and characterization of symptoms and risk factors related with the Chronic Obstructive Pulmonary Disease.