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

Rongmin Li; Jiaqi Yao; Haijian Chu; Da Ruan

doi:10.1007/s00500-009-0498-x

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

Rongmin Li
, Jiaqi Yao
, Haijian Chu
, Da Ruan

Research output › peer-review

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.

Original language	English
Pages (from-to)	1297-1303
Number of pages	7
Journal	Soft Computing
Volume	14
DOIs	https://doi.org/10.1007/s00500-009-0498-x
State	Published - 14 Nov 2009

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Good health and well being

Access to Document

10.1007/s00500-009-0498-xLicense: Unspecified

Cite this

@article{271b9b7ae4d84450b8f92345ed16e5ea,

title = "An optimal model of information diffusion principles to risk and decision analysis of breast cancer morbidity",

abstract = "Information diffusion methods (IDMs) often deal with {\textquotedblleft}small sample problems{\textquotedblright} 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 = "Information diffusion methods, Optimization, Fuzzy information, decision analysis, Morbidity",

author = "Rongmin Li and Jiaqi Yao and Haijian Chu and Da Ruan",

note = "Score=10",

year = "2009",

month = nov,

day = "14",

doi = "10.1007/s00500-009-0498-x",

language = "English",

volume = "14",

pages = "1297--1303",

journal = "Soft Computing",

issn = "1432-7643",

publisher = "Springer Science and Business Media Deutschland GmbH",

}

TY - JOUR

T1 - An optimal model of information diffusion principles to risk and decision analysis of breast cancer morbidity

AU - Li, Rongmin

AU - Yao, Jiaqi

AU - Chu, Haijian

AU - Ruan, Da

N1 - Score=10

PY - 2009/11/14

Y1 - 2009/11/14

N2 - 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.

AB - 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.

KW - Information diffusion methods

KW - Optimization

KW - Fuzzy information

KW - decision analysis

KW - Morbidity

UR - https://ecm.sckcen.be/OTCS/llisapi.dll/overview/38912954

U2 - 10.1007/s00500-009-0498-x

DO - 10.1007/s00500-009-0498-x

M3 - Article

SN - 1432-7643

VL - 14

SP - 1297

EP - 1303

JO - Soft Computing

JF - Soft Computing

ER -