Abstract
Data mining in health care include analysis, early detection, prevention of diseases, prevention of hospital errors, and for cost savings. The importance of machine learning has drastically increased due to predicting and diagnosing disease at an early stage. Due to slow convergence level and it requires a large amount of calculation for fuzzy neural network algorithm, a particle swarm optimization-based fuzzy neural network is used to solve classification of medical dataset. For this work, three medical datasets such as heart, lymph, and hepatitis are used for prediction of diseases. It is proven that there is a better classification rate while using PSO-based FNN.
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Sharmila, S.L., Poongothai, S. (2022). Disease Classification Using Particle Swarm Optimization with Fuzzy Neural Network. In: Peng, SL., Lin, CK., Pal, S. (eds) Proceedings of 2nd International Conference on Mathematical Modeling and Computational Science. Advances in Intelligent Systems and Computing, vol 1422. Springer, Singapore. https://doi.org/10.1007/978-981-19-0182-9_10
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DOI: https://doi.org/10.1007/978-981-19-0182-9_10
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