Introduction to medical data mining.
- Author:
Lingyun ZHU
1
;
Baoming WU
;
Changxiu CAO
Author Information
1. College of Automation, Chongqing University, Chonging 400044.
- Publication Type:Journal Article
- MeSH:
Algorithms;
Automatic Data Processing;
Databases, Factual;
Decision Making, Computer-Assisted;
Decision Trees;
Fuzzy Logic;
Information Storage and Retrieval;
methods;
Neural Networks (Computer)
- From:
Journal of Biomedical Engineering
2003;20(3):559-562
- CountryChina
- Language:Chinese
-
Abstract:
Modern medicine generates a great deal of information stored in the medical database. Extracting useful knowledge and providing scientific decision-making for the diagnosis and treatment of disease from the database increasingly becomes necessary. Data mining in medicine can deal with this problem. It can also improve the management level of hospital information and promote the development of telemedicine and community medicine. Because the medical information is characteristic of redundancy, multi-attribution, incompletion and closely related with time, medical data mining differs from other one. In this paper we have discussed the key techniques of medical data mining involving pretreatment of medical data, fusion of different pattern and resource, fast and robust mining algorithms and reliability of mining results. The methods and applications of medical data mining based on computation intelligence such as artificial neural network, fuzzy system, evolutionary algorithms, rough set, and support vector machine have been introduced. The features and problems in data mining are summarized in the last section.
