Abstract
Squamous cell carcinoma (SCC) is a type of skin malignancy. It is a fast growing skin disease which rapidly ravel to other parts of the body, if occurs in any particular body part. SCC is a genuinely moderate developing skin disease. Expert system tools such as fuzzy systems, neural networks and genetic algorithms are very useful in prediction of these diseases. In this paper we accordingly developed an approach by applying fuzzy logic technique on various parameters on the input dataset in order to predict the existence of squamous cell carcinoma among the patients. The fuzzy system accepts five information parameters for the data source and generates one yield parameter as an output. The output produced by this fuzzy logic system is analyzed to find the existence of squamous cell carcinoma and its stage. It is worth to mention that the simulation outcomes of the proposed system are better in terms of prediction accuracy of SCC as compared with other prediction techniques.
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Jha, S., Mehta, A.K., Azad, C. (2020). A Fuzzy Logic Based Approach for Prediction of Squamous Cell Carcinoma. In: Pant, M., Kumar Sharma, T., Arya, R., Sahana, B., Zolfagharinia, H. (eds) Soft Computing: Theories and Applications. Advances in Intelligent Systems and Computing, vol 1154. Springer, Singapore. https://doi.org/10.1007/978-981-15-4032-5_30
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DOI: https://doi.org/10.1007/978-981-15-4032-5_30
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