Abstract: In the molecular era the management of cancer is no more a plan based on simple guidelines. Clinical findings, tumor characteristics, and molecular markers are integrated to identify different risk categories, based on which treatment is planned for each individual case. This paper aims at developing a fuzzy decision support system (DSS) to guide the doctors for the risk stratification of breast cancer, which is expected to have a great impact on treatment decision and to minimize individual variations in selecting the optimal treatment for a particular case. The developed system was based on clinical practice of Oncology Center Mansoura University (OCMU). This system has six input variables (Her2, hormone receptors, age, tumor grade, tumor size, and lymph node) and one output variable (risk status). The output variable is a value from 1 to 4; representing low risk status, intermediate risk status and high risk status. This system uses Mamdani inference method and simulation applied in MATLAB R2009b fuzzy logic toolbox.

Ahmed Abou Elfetouh Saleh, Sherif Ebrahim Barakat and Ahmed Awad Ebrahim Awad, “ A Fuzzy Decision Support System for Management of Breast Cancer” International Journal of Advanced Computer Science and Applications(IJACSA), 2(3), 2011. http://dx.doi.org/10.14569/IJACSA.2011.020307

@article{Saleh2011,
title = { A Fuzzy Decision Support System for Management of Breast Cancer},
journal = {International Journal of Advanced Computer Science and Applications}
doi = {10.14569/IJACSA.2011.020307},
url = {http://dx.doi.org/10.14569/IJACSA.2011.020307},
year = {2011},
publisher = {The Science and Information Organization},
volume = {2},
number = {3},
author = {Ahmed Abou Elfetouh Saleh and Sherif Ebrahim Barakat and Ahmed Awad Ebrahim Awad},
}