DEVELOPING CASE-BASED REASONING FOR DISCOVERY OF BREAST CANCER

The treatment of early development of breast tumor has a higher success rate. This paper presents a framework for the early discovery of breast cancer. The objective is to assist the general practitioners and specialists in the detection of breast tumor. The proposed detection process consists of a preliminary screening process and a prediction process. The preliminary screening process using thermography aims to complement the detailed screening operation using mammography. The prediction process using artificial intelligence techniques aims to use past records of other similar cases to enhance the forecast of breast cancer development. The paper discusses the issues and techniques for the implementation of the proposed framework. These include the preliminary screening process, the retrieval of the relevant cases, and the prediction of the risk of developing breast cancer based on the thermographs, environmental/social data, physiological information, genetic factors, and medical records. This work constitutes initial effort to lessen the burden of medical professionals and increase the chances of successful treatment for patients in the fight against breast cancer.