Prediction of hidden knowledge from Clinical Database using data mining techniques
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 a...
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| Format: | Conference or Workshop Item |
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Institute of Electrical and Electronics Engineers Inc.
2014
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| Online Access: | https://www.scopus.com/inward/record.uri?eid=2-s2.0-84938790845&doi=10.1109%2fICCOINS.2014.6868414&partnerID=40&md5=15d3a467507e96430feedde1d43f0b81 http://eprints.utp.edu.my/31215/ |
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| Summary: | 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. |
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