Future of Healthcare: Machine Learning in Disease Prediction

Abstract

The disease prediction system is based on predictive modelling, which utilises the user's symptoms as input to identify the user's ailment. The system analyses the user's symptoms and returns the likelihood of the condition. Disease prediction is accomplished by putting the Random Forest, Decision Tree, and Naïve Bayer algorithms into practice. The likelihood of the sickness is determined by these algorithms. As big data expands in the biomedical and healthcare industries, accurate medical data analysis enhances patient care and early sickness diagnosis. This approach predicts illnesses using machine learning methods. Currently, disease prediction will be done using the decision tree method. The Random Forest and Naïve Bayer algorithms are being used to enhance.