A fuzzy logic based approach for prediction of basal cell carcinoma and squamous cell carcinoma among the data of skin cancer

A fuzzy logic based approach for prediction of basal cell carcinoma and squamous cell carcinoma among the data of skin cancer

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INTRODUCTION: Both basal cell carcinoma (BCC) and squamous cell carcinoma (SCC) is a type of skinmalignancy which are deadly in nature.Although both can cause a serious setback for the human body, SCC ismost dangerous as per human life is concerned.OBJECTIVES: It is necessary to spot out the cases of SCC and BCC among various data of skin cancer.In thisresearch, the same is spotted out with the help of the fuzzy logic system.METHODS: At first, the membership function is constructed from the input data provided.

Then based on thegenerated membership function, a set of fuzzy if-then rules 15-eg2373cl are created.The outliers from the source data arealso removed before the generation of the fuzzy membership function.Based on the fuzzy if-then rules, thedecision, whether the case is of basal cell or squamous cell carcinoma is taken.RESULTS: The output prediction by the system is compared with the actual pathological report of the patients.The comparison provides an accuracy of 94.

94 percent.CONCLUSION: This paper introduces a u11-200ps new technique to predict the existence of multiple cancers (either basalcell or squamous cell) from the mixed cancer dataset.The outcomes of the examination on the source datasetshow that the proposed system achieved extraordinary desire accuracy for the portrayal of squamous cellcarcinoma and basal cell carcinoma.