This work is dedicated to patients specially, rural patients can get to know the early stage detection of diseases before laboratory tests reducing the unlimited waiting time and cost expenditure. Clinical Decision Support System (CDSS) can be used for analyzing diseases to predict almost accurate disease automatically and patient's query. This work has been done with the help of a doctor as a human expert. We collected 300 sample data from patients. We have made the dataset from our sample

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... ent's information. Naïve Bayes classifier is used here to classify the diseases easily. The selected diseases are Malaria, Tuberculosis, Stroke, Fever, Diabetes, Heart disease. The prediction of a disease is measured with the prediction of a doctor before laboratory tests to get the system's accuracy. Here we got 100% accuracy on the trained dataset containing 180 cases.