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

被引：0

作者：

Santos, Maribel Yasmina ^{[1
]}

Goncalves, Diana ^{[1
]}

Cruz, Jorge ^{[2
]}

机构：

[1] Univ Minho, Algoritmi Res Ctr, Guimaraes, Portugal

[2] Univ Lisbon, Fac Med, Lisbon, Portugal

来源：

PROCEEDINGS OF THE 9TH WSEAS INTERNATIONAL CONFERENCE ON ARTIFICIAL INTELLIGENCE, KNOWLEDGE ENGINEERING AND DATA BASES | 2010年

关键词：

Knowledge discovery in databases; data mining; decision trees; primary hyperhidrosis; endoscopic thoracic sympathectomy; THORACOSCOPIC SYMPATHECTOMY; PRIMARY HYPERHIDROSIS; PALMAR HYPERHIDROSIS;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

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.

引用

页码：333 / +

页数：2