[Medical knowledge discovery system research based on computer--epidemiological data mining of complications in diabetes mellitus].
In this paper, a systematic architecture of medical data mining based on computer was provided for epidemiological analysis. Complications in diabetes mellitus were used as the cases under discussions on redundancy elimination, normalized storage, knowledge induction and visual expression of medical data. 3022 pieces of census records from Tianjin General Hospital were researched to find the solution of quantitative mining from qualitative data and knowledge discovery. From the qualitative data mining of 43 kinds of complications in diabetes mellitus, we found 18 knowledge rules with significant statistical meaning on concurrency relation, e. g. hyperlipoidemia, coronary disease, hypertension and cerebrovascular disease. And knowledge tree was noted to be an effective visual expression method for showing the rules generated from the above system. Medical analysis system based on data mining and knowledge discovery could generate effective knowledge rules from medical record database, which was found to be especially useful for epidemiological analysis and national health survey. So how to cooperate with community medical care and hospital information system in the near future is practically significant.
Yu
Hui
H
Department of Biomedical Engineering, Tianjin University, 300072, China.
Zhang
Lixin
L
Liu
Wenyao
W
D002681:China; D020000:Decision Support Systems, Clinical; D003661:Decision Support Techniques; D003663:Decision Trees; D048909:Diabetes Complications / Q000453:epidemiology*; D001330:Electronic Data Processing; D006801:Humans; D016347:Medical Records Systems, Computerized