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A hybrid approach of data mining and genetic algorithms for rehabilitation scheduling
Journal article   Peer reviewed

A hybrid approach of data mining and genetic algorithms for rehabilitation scheduling

Chen-Fu Chien, Yi-Chao Huang and Chin-Han Hu
International Journal of Manufacturing Technology and Management, Vol.16(1-2), pp.76-100
2009

Abstract

Attribute-oriented induction Data mining DM Gas Genetic algorithms Hospital management Physical therapy Physical therapy scheduling Rehabilitation scheduling Service engineering Service quality
To enhance the medical care quality and patient satisfaction, the hospital management has received considerable attention. This research aims to develop an intelligent approach that integrates Genetic Algorithm (GA) and Data Mining (DM) approaches to resolve the physical therapy scheduling problems to reduce patient waiting time and thus enhance service quality. In particular, this approach employed the attribute-oriented induction method to extract the patterns of the solutions generated from the GA approach. Thus, the decision rules derived from the patterns can be applied to resolve similar therapy scheduling problems with much lesser computational effort. The results of an empirical study conducted in a general hospital validated the practical viability of this approach. Copyright © 2009 Inderscience Enterprises Ltd.

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