Document Detail


Automated acquisition of rules from clinical databases and its evaluation.
MedLine Citation:
PMID:  10384535     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
This paper presents an approach to induction of rules from databases using rough set model. The system was evaluated on three clinical databases, and induced results were compared with other conventional rule induction methods and medical experts' rules. The results show that the introduced results outperforms other methods, but that the description length of induced rules is a little short, compared with that of experts' rules, which suggests that experts' rules are combination of different kinds of reasoning, rather than simple classification.
Authors:
S Tsumoto; H Tanaka
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Publication Detail:
Type:  Comparative Study; Journal Article    
Journal Detail:
Title:  Studies in health technology and informatics     Volume:  52 Pt 1     ISSN:  0926-9630     ISO Abbreviation:  Stud Health Technol Inform     Publication Date:  1998  
Date Detail:
Created Date:  1999-07-30     Completed Date:  1999-07-30     Revised Date:  2008-07-10    
Medline Journal Info:
Nlm Unique ID:  9214582     Medline TA:  Stud Health Technol Inform     Country:  CANADA    
Other Details:
Languages:  eng     Pagination:  649-53     Citation Subset:  IM    
Affiliation:
Department of Information Medicine, Tokyo Medical and Dental University, Japan.
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MeSH Terms
Descriptor/Qualifier:
Algorithms*
Classification / methods*
Database Management Systems*
Databases as Topic
Evaluation Studies as Topic
Expert Systems*
Humans
Information Theory
Probability

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine


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