C4.5: programs for machine learning
C4.5: programs for machine learning
MML clustering of multi-state, Poisson, vonMises circular and Gaussian distributions
Statistics and Computing
The platforms enabling wireless sensor networks
Communications of the ACM - Wireless sensor networks
On the Challenges and Opportunities of Pervasive and Ubiquitous Computing in Health Care
PERCOM '05 Proceedings of the Third IEEE International Conference on Pervasive Computing and Communications
Guest Editors' Introduction: Distributed Data Mining--Framework and Implementations
IEEE Internet Computing
Distributed data mining on clusters with bayesian mixture modeling
FSKD'05 Proceedings of the Second international conference on Fuzzy Systems and Knowledge Discovery - Volume Part I
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Ubiquitous Healthcare (u-healthcare) which focuses on automated applications that can provide healthcare to citizens anywhere/anytime using wired and wireless mobile technologies is becoming increasingly important. Ubiquitous healthcare data provides a mine of hidden knowledge which can be exploited in preventive care and "wellness" recommendations. Data mining is therefore a significant aspect of such systems. Distributed Data mining (DDM) techniques for knowledge discovery from databases help in the thorough analysis of data collected from healthcare facilities enabling efficient decision-making and strategic planning. This paper presents and discusses the development of a prototype ubiquitous healthcare system. The prospects for integrating data mining into this framework are studied using a distributed data mining system. The DDM system employs a mixture modelling mechanism for data partitioning. Initial results with some standard medical databases offer a plausible outlook for future integration.