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Expert system for breast cancer diagnosis: A survey

Breast cancer is leading cause of death and also one of the most invasive types of cancers among women in worldwide. It happens when cells in the breast start to develop uncontrollably or spread throughout the body. Early detection and effective diagnosis is the only rescue to lessen breast cancer fatality. Accurate classification of breast tumor is an important task in medical diagnosis. Soft computing approaches are gaining importance in medical disease diagnosis because of their classification performance. The goal of this survey paper is to determine the current state of research in breast cancer and to help extract the key features and problems with existing expert systems. There are many numbers of quantitative models based on support vector machine, neural network, fuzzy logic, hybrid and many others techniques are being operated in medical field to help decision makers in breast cancer prevention. The comparison of the various systems is done on the basis of data sets used for diagnosis, the methodology applied and the platform on which the system is implemented. Thus this paper reviews the various expert systems from 1996 to 2015 used for breast cancer disease diagnosis.