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The thyroid, an endocrine gland that secretes hormones in the blood,circulates its products to all tissues of the body, where they control vitalfunctions in every cell. Normal levels of thyroid hormone help the brain,heart, intestines, muscles and reproductive system function normally. Thyroidhormones control the metabolism of the body. Abnormalities of thyroid functionare usually related to production of too little thyroid hormone(hypothyroidism) or production of too much thyroid hormone (hyperthyroidism).Therefore, the correct diagnosis of these diseases is very important topic. Inthis study, Linguistic Hedges Neural-Fuzzy Classifier with Selected Features(LHNFCSF) is presented for diagnosis of thyroid diseases. The performanceevaluation of this system is estimated by using classification accuracy andk-fold cross-validation. The results indicated that the classification accuracywithout feature selection was 98.6047% and 97.6744% during training and testingphases, respectively with RMSE of 0.02335. After applying feature selectionalgorithm, LHNFCSF achieved 100% for all cluster sizes during training phase.However, in the testing phase LHNFCSF achieved 88.3721% using one cluster foreach class, 90.6977% using two clusters, 91.8605% using three clusters and97.6744% using four clusters for each class and 12 fuzzy rules. The obtainedclassification accuracy was very promising with regard to the otherclassification applications in literature for this problem.

Expert System Based On Neural-Fuzzy Rules for Thyroid Diseases Diagnosis