الفهرس 
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Abstract
Worldwide, breast cancer is the second most common type of cancer after lung cancer and the fifth most common cause of cancer death.
Decision support system (DSS) is an intelligent model dealing with semi- or ill-defined and structured decision-making problems in order to support better judgment amongst decision-makers.
DSS brings many benefits, increased productivity, understanding, speed and flexibility, reduced problem complexity, and cost.
DSS applied on many domains one of them is medical decision support systems, which are computer applications designed to aid clinicians in making diagnostic and therapeutic decisions in patient care.
One of the most important branches of medical that DSS is applied is cancer care.
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.
The diagnosis of disease including cancer involves several levels of uncertainty and imprecision as HER2-neu positivity, hormone receptor (negative-weak positive, weak positive-moderate positive & moderate positive-strong positive), etc. In real life, things are not either black or white, but most of the times are grey. Thus, in many practical situations, it is convenient to consider intermediate logical values.
Uncertainty is now considered essential to science and fuzzy logic is a way to model and deal with it using natural language. We can say that fuzzy logic is a qualitative computational approach. Fuzzy logic is a method to render precise what is imprecise in the world of medicine.
This thesis aims to conduct data analysis of different patients’ and tumors’ characteristics to develop a web based fuzzy decision support system (DSS) to guide the oncologists for the risk stratification of cancer, applied here in 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 in situations of certainty and uncertainty. This system called Decision Support System for Cancer (DSSC).
The developed system was based on clinical practice of Oncology Center Mansoura University (OCMU).
DSSC used fuzzy logic technique with ASP. Net 4 (based on VB.Net language), AJAX, Jscript and Microsoft SQL Server 2008 and Matlab for experiment.
DSSC provides high success in diagnosis and treatment of cancer than traditional manners.