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Ontology Based System for Prediction of Diseases

In today’s world of lifestyle, biomedical and healthcare act the main role through which disease in the patient can be identified. However, the current solution focuses on communities where the accurate prediction plays a major role to find out risk of the disease in the patient. The detection of disease is done by using prediction algorithm. Here, machine-learning algorithm is has been used to find the accuracy. The dataset has been is collected from certain hospitals and pre-processed where the missing values have been reconstructed before prediction process. Due to the huge amount of information in healthcare, the accurate result is the need for disease recognition and services. Generally raw data has bad quality because it does have exactness, completeness of records fields. Moreover, there would be different exhibits in different regions, the appearances of certain diseases, which may also weaken the prediction of the disease outbreak. Using the health record, our system received the rate of accuracy is 97%. In this proposed system, we provides prediction of various diseases that occurs through using machine learning that will be effective. In urban lifestyle, modern large cities have significant adverse effects on health, & increasing risk of diseases.