Abstract
Detailed elaborations are presented for the idea on ID3 algorithm of Decision Tree. An improved method called Improved ID3 algorithm that can improve the speed of generation is brought forward owing to the disadvantages of ID3 algorithm. Moreover, based on Improved ID3 algorithm, data mining for breast-cancers is carried out for primarily predicting the relationship between recurrence and other attributes of breast cancer by making use of SQL Server 2005 Analysis Services. Results prove the effectiveness of Decision Tree in medical data mining which provide physicians with diagnostic assistance.
Highlights
Used of computer information management system in medical institutions promotes the digitization of medical information and expands the information capacity in the hospital database
A trial of medical data mining was made on 285 cases of breast disease patients in HIS (Hospital Information System) using Decision Tree algorithm
The decision tree is built by the ID3 algorithm, and the process is as follows (ZOU Yuan, 2010): (1) Create a node N. (2) If the samples of the node belong to the same class C, return N is a classification for the C of leaf nodes
Summary
Used of computer information management system in medical institutions promotes the digitization of medical information and expands the information capacity in the hospital database. These precious hospital information resources are valuable to medical diagnosis, treatment and medical research (Du Haizhou, 2009, pp.163167). The new problem for promoting the development of hospital and service quality is that, how to automatically upgrade and process the medical database, to provide comprehensive and accurate diagnostic decision-making and health measures. In this context, medical data mining emerged (ZHAO Xiao-fan, 2011, pp.292294). A trial of medical data mining was made on 285 cases of breast disease patients in HIS (Hospital Information System) using Decision Tree algorithm
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