Multiple Disease Prediction Using Machine Learning

Abstract

Machine learning, which is a type of computer technology, has changed healthcare a lot. It helps doctors predict diseases better and faster. In healthcare, using machine learning algorithms decision tree (DT), logistic regression (LR), support vector machine (SVM) that can help predict lots of different diseases at the same time. This helps doctors find and treat illnesses early, which makes patients better and saves money on healthcare. This paper looks at how we can use computer programs that learn from data to predict many diseases. It talks about why this is good, what problems we might face, and where we might go next with it. We give a summary of the several machine learning models and information sources that are often employed in illness prediction. We also go over the significance of feature selection, model assessment, and combining several data modalities for improved illness prediction. We give a summary of the several machine learning models and information sources that are often employed in illness prediction. We also go over the significance of feature selection, model assessment, and combining several data modalities for improved illness prediction. The research shows that using machine learning algorithms to predict many diseases at once could really help public health. Again, we use a machine learning model to determine whether or not an individual is impacted by a few diseases. This training model trains itself to predict illness using sample data.