Mining Healthcare Data: The Case of an Endoscopic Thoracic Sympathectomy Dataset

The process of knowledge discovery in databases aims at the discovery of associations within data in a dataset. Data Mining is a central step of this process corresponding to the application of algorithms for identifying patterns in data. This paper presents the particular case of analysis of a dataset containing data associated with 227 patients submitted to an endoscopic thoracic sympathectomy, a treatment for primary palmar hyperhidrosis. Primary hyperhidrosis is characterized by an excessive sweating that appears as a consequence of a disorder of the sympathetic autonomous nervous system The results achieved show an overall improvement of the patients' quality of life, mainly associated with their emotional state.