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

(2010) SOFT COMPUTING. 14(12). p.1297-1303
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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.
Keywords
FUZZY-SETS, Morbidity, SYSTEM, Decision analysis, Fuzzy information, Information diffusion methods, Optimization

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MLA
Li, Rongmin, Jiaqi Yao, Hanji Shang, et al. “An Optimal Model of Information Diffusion Principles to Risk and Decision Analysis of Breast Cancer Morbidity.” SOFT COMPUTING 14.12 (2010): 1297–1303. Print.
APA
Li, Rongmin, Yao, J., Shang, H., & Ruan, D. (2010). An optimal model of information diffusion principles to risk and decision analysis of breast cancer morbidity. SOFT COMPUTING, 14(12), 1297–1303. Presented at the 3rd International conference on Intelligent System and Knowledge Engineering.
Chicago author-date
Li, Rongmin, Jiaqi Yao, Hanji Shang, and Da Ruan. 2010. “An Optimal Model of Information Diffusion Principles to Risk and Decision Analysis of Breast Cancer Morbidity.” Soft Computing 14 (12): 1297–1303.
Chicago author-date (all authors)
Li, Rongmin, Jiaqi Yao, Hanji Shang, and Da Ruan. 2010. “An Optimal Model of Information Diffusion Principles to Risk and Decision Analysis of Breast Cancer Morbidity.” Soft Computing 14 (12): 1297–1303.
Vancouver
1.
Li R, Yao J, Shang H, Ruan D. An optimal model of information diffusion principles to risk and decision analysis of breast cancer morbidity. SOFT COMPUTING. 2010;14(12):1297–303.
IEEE
[1]
R. Li, J. Yao, H. Shang, and D. Ruan, “An optimal model of information diffusion principles to risk and decision analysis of breast cancer morbidity,” SOFT COMPUTING, vol. 14, no. 12, pp. 1297–1303, 2010.
@article{2918507,
  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.},
  author       = {Li, Rongmin and Yao, Jiaqi and Shang, Hanji and Ruan, Da},
  issn         = {1432-7643},
  journal      = {SOFT COMPUTING},
  keywords     = {FUZZY-SETS,Morbidity,SYSTEM,Decision analysis,Fuzzy information,Information diffusion methods,Optimization},
  language     = {eng},
  location     = {Xiamen, PR China},
  number       = {12},
  pages        = {1297--1303},
  title        = {An optimal model of information diffusion principles to risk and decision analysis of breast cancer morbidity},
  url          = {http://dx.doi.org/10.1007/s00500-009-0498-x},
  volume       = {14},
  year         = {2010},
}

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