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- W2996838346 abstract "The aim of this study is to present novel algorithms for prediction of dermatological disease using only dermatological clinical features and diagnoses collected in real conditions. A combination of the Adaptive Neuro-Fuzzy Inference Systems (ANFIS) and Genetic algorithm (GA) for ANFIS subtractive clustering parameter optimization has been suggested for the first level of fuzzy model optimization. After that, a genetic optimized ANFIS fuzzy structure is used as input in GA for the second level of fuzzy model optimization. We used double 2-fold Cross validation for generating different validation sets for model improvements. Our approach is performed in the MATLAB environment. We compared results with the other studies. The results confirm that the proposed model achieves accuracy rates which are higher than the one with the previous model." @default.
- W2996838346 created "2020-01-10" @default.
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- W2996838346 date "2017-01-01" @default.
- W2996838346 modified "2023-09-23" @default.
- W2996838346 title "Dermatology Disease Prediction Based on Two Step Cascade Genetic Algorithm Optimization of ANFIS Parameters." @default.
- W2996838346 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/28423766" @default.
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