Abstract
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.
Keywords
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
Znati, T.: On the challenges and opportunities of pervasive and ubiquitous computing in health care. In: Proceedings of the IEEE International Conference on Pervasive Computing and Communications - PerCom 2005, Kauai Island, HI, USA, Mar. 2005, p. 396 (2005)
MobileHealth: http://www.mobihealth.org/
EliteCare: http://www.elitecare.com/index.html
Tele-Monitoring: http://www.medical.philips.com
Van Laerhoven, K., et al.: Medical Healthcare Monitoring with Wearable and Implantable Sensors. In: 2nd International Workshop on Ubiquitous Computing for Pervasive Healthcare Applications (2004)
Smart Medical Home, http://www.futurehealth.rochester.edu/smart_home/Smart_home.html
Hill, J., Horton, M., Kling, R., Krishnamurthy, L.: The Platforms enabling Wireless Sensor Netowrks. Communications of the ACM 47, 41–46 (2004)
Jardine, I., Clough, K.: The Impact of Telemedicine and Telecare on Healthcare. Journal of Telemedicine and Telecare 5(Suppl. 1), 127–128 (1999)
Smithers, C.R., Hill, N.: Options for Wireless Technology in Telemedicine and Telecare Applications. Journal of Telemedicine and Telecare 5(Suppl. 1), 138–139 (1999)
Kumar, A., Kantardzic, M.: Distributed Data Mining: Framework and Implementations. IEEE Internet Computing 10(4), 15–17 (2006)
Park, B.H., Kargupta, H.: Distributed data mining: Algorithms, systems, and applications. In: Ye, N. (ed.) The Handbook of Data Mining, Lawrence Erlbaum, Mahwah (2003)
Wallace, C.S., Dowe, D.L.: MML clustering of multi-state, Poisson, von Mises circular and Gaussian distributions. Statistics and Computing 10(1), 73–83 (2000)
Message Passing Interface Forum: MPI: A message-passing interface standard. International Journal of Supercomputer Applications 8(3/4), 165–414 (1994)
Quinlan, J.R.: C4.5: Programs for machine learning. Morgan Kaufmann, San Mateo (1993)
Viswanathan, M., Yang, Y.K., Whangbo, T.K.: Distributed Data Mining on Clusters with Bayesian Mixture Modeling. In: Wang, L., Jin, Y. (eds.) FSKD 2005. LNCS (LNAI), vol. 3613, pp. 1207–1216. Springer, Heidelberg (2005)
Merz, C., Murphy, P.: UCI repository of machine learning databases. A.B. Smith, C.D. Jones, and E.F. Roberts, "Article Title", Journal, Publisher, Location, Date, pp. 1-10 (1998)
Kraft, M.R., Desouza, K.C., Androwich, I.: Data Mining in Healthcare Information Systems: Case Study of a Veterans’ Administration Spinal Cord Injury Population (2000)
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 2007 Springer Berlin Heidelberg
About this paper
Cite this paper
Viswanathan, M. (2007). Distributed Data Mining in a Ubiquitous Healthcare Framework. In: Kobti, Z., Wu, D. (eds) Advances in Artificial Intelligence. Canadian AI 2007. Lecture Notes in Computer Science(), vol 4509. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-72665-4_23
Download citation
DOI: https://doi.org/10.1007/978-3-540-72665-4_23
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-72664-7
Online ISBN: 978-3-540-72665-4
eBook Packages: Computer ScienceComputer Science (R0)