Prediction of chronic disease using deep learning

Abstract

In present times, people are exposed to various illnesses due to their lifestyle and the state of the environment. It is crucial to identify and predict these diseases at an early stage to prevent their progression to a more severe state. The goal of this proposed work is to identify and predict the patients with more common chronic illness. The prediction gives the benefit of early disease detection. In this proposed work, prediction is done by deep learning. The paper propose a deep learning approach for predicting chronic diseases using a convolution neural network (CNN) model. The system comprise three modules: an admin module, a doctor module and a patient module. The admin module provides an interface for managing patient data, while the doctor module allows doctor to access patient data and generate reports. The patient module allows the patient to input their health data and receive personalized health recommendations. The CNN model is used to learn complex pattern in the patient data and predict the risk of chronic disease. The proposed system has the potential to improve the accuracy of chronic disease prediction, enabling early intervention and prevention of these diseases.