In this paper different classification methods are compared using base and meta(Combination of Multiple Classifier for training) level classifiers, for the fruitful diagnosis of Lower Back Pain. The Lower Back Pain becomes chronic with age, so needs to be correctly diagnose with symptoms in the early age. Five independent classifiers were implemented at base level and meta level. At meta level, five combinations of different classifiers were implemented, using voting technique. According to the scores, the overall classification using Naïve Bayes and Multilayer Perceptron got the maximum efficiency 83.87%. The purpose of this paper is to diagnose healthy individuals efficiently. To carry out study the Lower Back Pain Symptoms Dataset is used from very famous platform for predictive modeling, Kaggle. The experiments were carried out in WEKA (Waikato Environment for Knowledge Analysis), suite of machine learning software1.

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An Expert System is a system that generates responses on the basis of expert knowledge base. Its application area covers fields like an organization's strategic impression, based on decision making to, in medical field where, decisions are going to made for diagnosing a disease, to providing assistance for the treatment of diagnosed disease.Here in this paper we are going to review the applications of an Expert System in different areas of medical field like radiology, allopathic medicine, and homeopathy.