Early Disease Prediction using Ml

Abstract

The approach employed in disease prediction using machine learning involves making forecasts about various diseases by utilizing symptoms provided by patients or other individuals. The supervised machine learning approaches called random forest classifier, KNN classifier, SVMs classifier are employed to forecast the disease. These algorithms are used to determine the disease's probability. Accurate medical data analysis helps with patient care and early disease identification as biomedical and healthcare data volumes rise. Diabetes, heart diseases are just a few of the illnesses we can forecast using linear regression and decision trees. Early detection is beneficial for determining the possibility of diabetes, heart disease.