Prediction of hidden knowledge from Clinical Database using data mining techniques

Thangarasu, G. and Dominic, P.D.D. (2014) Prediction of hidden knowledge from Clinical Database using data mining techniques. In: UNSPECIFIED.

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Clinical Database has enormous quantity of information about patients and their diseases. The database mainly contains clinical consultation details, family history, medical lab report and other information which are considered to taking a final diagnostic decision by physician. Clinical databases are widely utilized by the numerous researchers for predicting different diseases. The current diabetes diagnosis methods are carried out based on the impact of various medical test and the results of physical examination. The new and innovative prediction methods are projected in this research to identify the diabetic disease, its types and complications from the clinical database in an efficiently and an economically faster manner. © 2014 IEEE.

Item Type: Conference or Workshop Item (UNSPECIFIED)
Impact Factor: cited By 9
Uncontrolled Keywords: Clinical research; Cluster analysis; Clustering algorithms; Database systems; Diagnosis; Forecasting; Fuzzy logic; Genetic algorithms; Neural networks, Clinical database; Data clustering; Diabetes diagnosis; Diagnostic decisions; Hidden knowledge; Hybrid genetic algorithms; Prediction methods, Data mining
Depositing User: Ms Sharifah Fahimah Saiyed Yeop
Date Deposited: 25 Mar 2022 09:03
Last Modified: 25 Mar 2022 09:03

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