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An optimal model of information diffusion principles to risk and decision analysis of breast cancer morbidity

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Abstract

Information diffusion methods (IDMs) often deal with “small sample problems” and distribute the information of one data point to its neighbors in fuzzy information processing. By considering new criteria, we establish an optimal model for parameters of IDMs to risk and decision analysis of fatal disease. We further illustrate a specific process and a successful application of IDMs by a more reasonable morbidity surface from one-dimensional and two-dimensional case studies of breast cancer analysis in Yanpu District, Shanghai.

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Acknowledgments

This work was supported by the National Basic Research Program of China (973 Program) under the Grant No. 2007CB814904. Authors also thank Dr. Anle Li for his help in completing this paper.

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Authors and Affiliations

  1. School of Mathematical Sciences, Fudan University, 220 Handan Road, Shanghai, People’s Republic of China

    Rongmin Li, Jiaqi Yao & Hanji Shang

  2. Belgian Nuclear Research Centre (SCK•CEN), Boeretang 200, 2400, Mol, Belgium

    Da Ruan

  3. Department of Applied Mathematics and Computer Science, Ghent University, Krijsglaan 281-S9, 9000, Ghent, Belgium

    Da Ruan

Authors
  1. Rongmin Li
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  2. Jiaqi Yao
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  3. Hanji Shang
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  4. Da Ruan
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Correspondence to Rongmin Li.

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Li, R., Yao, J., Shang, H. et al. An optimal model of information diffusion principles to risk and decision analysis of breast cancer morbidity. Soft Comput 14, 1297–1303 (2010). https://doi.org/10.1007/s00500-009-0498-x

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  • DOI: https://doi.org/10.1007/s00500-009-0498-x

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