Affiliation:
1. Flinders University of South Australia, Adelaide, South Australia
2. Health Insurance Commission, Canberra, ACT, Australia
Abstract
The application of data mining and knowledge discovery techniques to medical and health datasets is a rewarding but highly challenging area. Not only are the datasets large, complex, heterogeneous, hierarchical, time-varying and of varying quality but there exists asubstantial medical knowledge base which demands a robust collaboration between the data miner and the health professional(s) if useful information is to be extracted.This paper presents the experiences of the authors and others in applying exploratory data mining techniques to medical, health and clinical data. In so doing, it elicits a number of general issues and provides pointers to possible areas of future research in data mining and knowledge discovery more broadly.
Publisher
Association for Computing Machinery (ACM)
Cited by
35 articles.
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