Object-oriented development of a concept learning system for time-centered clinical data
Journal of Medical Systems
An Apriori-Based Algorithm for Mining Frequent Substructures from Graph Data
PKDD '00 Proceedings of the 4th European Conference on Principles of Data Mining and Knowledge Discovery
A delivery framework for health data mining and analytics
ACSC '05 Proceedings of the Twenty-eighth Australasian conference on Computer Science - Volume 38
Uniqueness of medical data mining
Artificial Intelligence in Medicine
Data Mining in Tourism Demand Analysis: A Retrospective Analysis
ADMA '07 Proceedings of the 3rd international conference on Advanced Data Mining and Applications
AI'06 Proceedings of the 19th Australian joint conference on Artificial Intelligence: advances in Artificial Intelligence
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Medical Data Mining is a very active and challenging research area in Data Mining community. However researchers entering Medical Data Mining should be aware that in core clinical, dentistry and nursing, data mining is not welcomed as much as we believe and publication of results in these journals based on Data Mining algorithms is not easily possible. In this paper, in addition to presenting one of our “successful” KDD projects in Urology that did not get to anywhere, we back up our belief based on designed searches on PubMed and review literature based on these searches. Our findings suggest that few Data Mining algorithms made their ways into core clinical journals. The paper concludes by reasons we have collected through our experiences.