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Improving diagnostic accuracy using agent-based distributed data mining system.
MedLine Citation:
PMID:  22958198     Owner:  NLM     Status:  Publisher    
Abstract/OtherAbstract:
The use of data mining techniques to improve the diagnostic system accuracy is investigated in this paper. The data mining algorithms aim to discover patterns and extract useful knowledge from facts recorded in databases. Generally, the expert systems are constructed for automating diagnostic procedures. The learning component uses the data mining algorithms to extract the expert system rules from the database automatically. Learning algorithms can assist the clinicians in extracting knowledge automatically. As the number and variety of data sources is dramatically increasing, another way to acquire knowledge from databases is to apply various data mining algorithms that extract knowledge from data. As data sets are inherently distributed, the distributed system uses agents to transport the trained classifiers and uses meta learning to combine the knowledge. Commonsense reasoning is also used in association with distributed data mining to obtain better results. Combining human expert knowledge and data mining knowledge improves the performance of the diagnostic system. This work suggests a framework of combining the human knowledge and knowledge gained by better data mining algorithms on a renal and gallstone data set.
Authors:
S Sridhar
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Publication Detail:
Type:  JOURNAL ARTICLE     Date:  2012-9-7
Journal Detail:
Title:  Informatics for health & social care     Volume:  -     ISSN:  1753-8165     ISO Abbreviation:  Inform Health Soc Care     Publication Date:  2012 Sep 
Date Detail:
Created Date:  2012-9-10     Completed Date:  -     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  101475011     Medline TA:  Inform Health Soc Care     Country:  -    
Other Details:
Languages:  ENG     Pagination:  -     Citation Subset:  -    
Affiliation:
Department of Information Science and Technology , Anna University , Chennai 600025 , India.
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