Self-Health Analysis with Two Step Histogram based Procedure using Machine Learning

Abstract

Machine learning is the critical tool in the future for prediction in the real-time to analyze the self-health of the person. The self-health is the motivation for the patient who is suffering from different health issues and unaware of those because of not having the accurate backup or motivation. This article presents the two-step histogram-based procedure using machine learning where patient can get the idea on what's their current position in their health. The histogram methodology will be working in the two-stage mechanism which is the proposed methodology. The result of histogram methodology achieved 95% accuracy in identifying the self-health of the person. There will a user interface where he can communicate with the model by user inputs and the algorithm behind the submit button can analyse the self-health of the patient. There is a behavior for the patient to give the false inputs to the model and there is a risk analysis in the model which is an in build to analyse the accurate relativity of the inputs given by the patients to the application. The proposed method obtained 95% accuracy and the two-step histogram methodology can help the self to analyse their own health condition using machine learning models.

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