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In this study, a hybrid method based on an Adaptive Neuro-Fuzzy InferenceSystem (ANFIS) and Particle Swarm Optimization (PSO) for diagnosing Liverdisorders (ANFIS-PSO) is introduced. This smart diagnosis method deals with acombination of making an inference system and optimization process which triesto tune the hyper-parameters of ANFIS based on the data-set. The Liver diseasescharacteristics are taken from the UCI Repository of Machine LearningDatabases. The number of these characteristic attributes are 7, and the samplenumber is 354. The right diagnosis performance of the ANFIS-PSO intelligentmedical system for liver disease is evaluated by using classification accuracy,sensitivity and specificity analysis, respectively. According to theexperimental results, the performance of ANFIS-PSO can be more considerablethan traditional FIS and ANFIS without optimization phase.

Hybrid Adaptive Neuro-Fuzzy Inference System for Diagnosing the Liver Disorders