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Knowledge Extraction Algorithm for Variances Handling of CP Using Integrated Hybrid Genetic Double Multi-group Cooperative PSO and DPSO

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Abstract

Although the clinical pathway (CP) predefines predictable standardized care process for a particular diagnosis or procedure, many variances may still unavoidably occur. Some key index parameters have strong relationship with variances handling measures of CP. In real world, these problems are highly nonlinear in nature so that it’s hard to develop a comprehensive mathematic model. In this paper, a rule extraction approach based on combing hybrid genetic double multi-group cooperative particle swarm optimization algorithm (PSO) and discrete PSO algorithm (named HGDMCPSO/DPSO) is developed to discovery the previously unknown and potentially complicated nonlinear relationship between key parameters and variances handling measures of CP. Then these extracted rules can provide abnormal variances handling warning for medical professionals. Three numerical experiments on Iris of UCI data sets, Wisconsin breast cancer data sets and CP variances data sets of osteosarcoma preoperative chemotherapy are used to validate the proposed method. When compared with the previous researches, the proposed rule extraction algorithm can obtain the high prediction accuracy, less computing time, more stability and easily comprehended by users, thus it is an effective knowledge extraction tool for CP variances handling.

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Acknowledgements

This work described in this paper was supported by Research Grant from National Natural Science Foundation of China (60774103) and Major Program Development Fund of SJTU. Moreover, we would also like to thank to the whole medical staff of Shanghai No. 6 People’s Hospital for real data collecting and helpful discussions. We also wish to thank the journal editor and the three referees for their detailed and helpful comments to improve the paper.

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Authors and Affiliations

  1. Department of Industrial Engineering & Logistics Management, School of Mechanical Engineering, Shanghai Jiao Tong University, 800 Dong Chuan Road, Shanghai, 200240, China

    Gang Du & Zhibin Jiang

  2. Shanghai Putuo District Central Hospital, Shanghai, 200062, China

    Xiaodi Diao

  3. Shanghai No. 6 People’s Hospital, Shanghai, 200233, China

    Yang Yao

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  1. Gang Du
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  2. Zhibin Jiang
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  3. Xiaodi Diao
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  4. Yang Yao
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Correspondence to Zhibin Jiang.

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Du, G., Jiang, Z., Diao, X. et al. Knowledge Extraction Algorithm for Variances Handling of CP Using Integrated Hybrid Genetic Double Multi-group Cooperative PSO and DPSO. J Med Syst 36, 979–994 (2012). https://doi.org/10.1007/s10916-010-9562-4

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  • DOI: https://doi.org/10.1007/s10916-010-9562-4

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