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Application of Machine Learning Techniques to Differential Diagnosis of Erythemato-Squamous Diseases

This paper is about the implementation of a visual tool for Differential Diagnosis of Erythemato-Squamous Diseases based on the classification algorithms; Nearest Neighbor Classifier (NN), Naive Bayesian Classifier using Normal Distribution (NBC) and Voting Feature Intervals-5 (VFI5). This tool enables the doctors to differentiate six types of ErythematoSquamous Diseases using clinical and histopathological parameters obtained from a patient. The program also gives explanations for the classifications of each classifier.