alexa Abstract | Implementation of Evolutionary Computing Techniques for Cancer Diagnosis Using Digital Signal Processor
ISSN ONLINE(2319-8753)PRINT(2347-6710)

International Journal of Innovative Research in Science, Engineering and Technology
Open Access

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Research Article Open Access


This paper presents a novel approach to implement Evolutionary Computing (EI) techniques like Fuzzy Logic, Genetic Algorithm, Neural Network, and Adoptive Neuro-Fuzzy Inference System (ANFIS) for diagnosis of cancer using TMS320C6713 (Texas Instruments) DSP (Digital Signal Processor). The simulator has been developed using MATLAB and Neurosolution, while implementation has been done using code composer studio for TMS320C6713 DSP. Performance is compared by considering the metrics like accuracy of diagnosis and mean square error. The simulation and implementation result show that this EI approach can be effectively used for cancer detection to help oncologist to enhance the survival rates significantly.

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Author(s): Dr. Rajendra D. Kanphade, Devesh D. Nawgaje


Evolutionary Computing, Fuzzy Logic, Genetic Algorithm, Neural Network, Adaptive Neuro Fuzzy Inference System, Digital Signal Processor, Scientific Computing,Signal Transduction,Cancer Signaling Array,Cell Signal

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