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 data...
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| Other Authors: | , |
| Format: | conferencePaper |
| Language: | eng |
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2010
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| Subjects: | |
| Online Access: | http://hdl.handle.net/1822/11367 |
| Country: | Portugal |
| Oai: | oai:repositorium.sdum.uminho.pt:1822/11367 |
| Summary: | 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. |
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