Discovery of association rules in medical data

Data mining is a technique for discovering useful information from large databases. This technique is currently being profitably used by a number of industries. A common approach for information discovery is to identify association rules which reveal relationships among different items. In this pape...

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Bibliographic Details
Published in:Medical informatics and the internet in medicine 2001, Vol.26 (1), p.25-33
Main Authors: DODDI, Srinivas, MARATHE, Achla, RAVI, S. S, TORNEY, David C
Format: Article
Language:English
Subjects:
Algorithms
Biological and medical sciences
Computerized medical documentation
Computerized, statistical medical data processing and models in biomedicine
Confidence Intervals
Databases, Factual
Diagnosis-Related Groups
Humans
Information Storage and Retrieval - methods
Medical Informatics Applications
Medical Informatics Computing
Medical Records Systems, Computerized
Medical sciences
Natural Language Processing
Random Allocation
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Summary:Data mining is a technique for discovering useful information from large databases. This technique is currently being profitably used by a number of industries. A common approach for information discovery is to identify association rules which reveal relationships among different items. In this paper, we use this approach to analyse a large database containing medical-record data. Our aim is to obtain association rules indicating relationships between procedures performed on a patient and the reported diagnoses. Random sampling was used to obtain these association rules. After reviewing the basic concepts associated with data mining, we discuss our approach for identifying association rules and report on the rules generated.
ISSN:1463-9238
1464-5238
DOI:10.1080/14639230010028786