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Automated Intelligent Diagnostic Liver Disorders Based on Adaptive Neuro Fuzzy Inference System and Fuzzy C-Means Techniques

Mody University International Journal of Computing and Engineering Research

Volume 2 Issue 2

Published: 2018
Author(s) Name: Haneet Kour, Amit Sharma, Jatinder Manhas and Vinod Sharma | Author(s) Affiliation: Department of Computer Science & IT, University of Jammu, Jammu, India.
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Abstract

Liver disorders are most common in the world in recent times. In this study, an automated intelligent diagnostic approach has been proposed to indicate the liver disease by various sorts and separating facts of the disease using Adaptive Neuro Fuzzy Inference System (ANFIS) and Fuzzy C-Means (FCM) techniques. The data required to study has been chosen by more complex Neuro Fuzzy Model before its inspection on the clinical data. In order to ensure the adeptness of the physician, diagnosing the liver disease and prescribing the absence of sensational ways is very energetic assignment. To make the process more meaningful and scientific a data of about 583 patients, who were undergoing treatment of the doctors in various hospitals, is collected. Since the study includes the detailed information of the patient, so pre-processing was done. The Neuro Fuzzy techniques have been applied over the patient data. The results of these valuation show that Neuro Fuzzy technique can be applied successfully for advising the anesthetic for liver disease patient.

Keywords: AI, ANFIS, FCM, Machine learning, Neuro fuzzy.

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