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Prediction of risk in breast cancer using fuzzy logic tool box in Matlab environment

Author: 
Valarmathi, S., Ayesha Sulthana, Ramya Rathan, Latha, K. C., Balasubramanian, S. and Sridhar, R.
Subject Area: 
Health Sciences
Abstract: 

Breast cancer risk assessment in western region of Tamil Nadu in India was carried out based on TNM (Tumor, Number of Lymph Nodes and Metastasis) staging using ID3 algorithm and Association rule. The intensity range of the breast cancer was predicted using Fuzzy logic toolbox. Out of 1,862 data the complete history of 181 breast cancer cases was obtained. The parameters involved in this study were age, sex, location, diet, year, marital status, heredity, period of illness, treatment, stages of diagnosis like Tumor [T], Number of Lymph Nodes [N] and Metastasis [M]. Eight set of fuzzy rules were used, the Mamdani max-min inference mechanism was implemented. Tumor size, number of nodes and the metastasis were used as input parameters and the breast cancer risk was obtained as an output. For fuzzification of these parameters the linguistic variables Very Serious (VS), Very Serious Moderate (VSM), Serious (S) and Not Serious (NS) were used in order to give a breast cancer risk prognosis. High breast cancer risk regions in the study area were shown in map using ID3 algorithm, Coimbatore (North and South) was found to be at highest risk for breast cancer by 20% criteria in comparison with other areas. However, this 20% criteria value in the association rule showed 18 taluks including Coimbatore to be the risk regions for breast cancer. Fuzzy Expert System (FES) predicted range of the risk of the breast cancer was found to be similar with the clinical truth.

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