Abstract
The medical field regularly handles enormous amounts of data. Handling huge data by conventional methods can affect the results. Algorithms for machine learning can be used to find out facts in medical research, in particular for disease prediction. The early recognition of disease is crucial for the analysis of patient medicines and specialists. Machine learning algorithms like Decision trees, Support vector machine, Multilayer perceptron, Bayes classifiers, K-Nearest Neighbors Ensemble classifier techniques etc are used to determine various ailments. Using machine learning algorithms can lead to rapid disease prediction with high accuracy. This research paper analyzes how machine learning techniques are used to predict different diseases and its types. This paper examined research papers focusing mainly on the prediction of chronic kidney disease, machine learning, heart disease, diabetes, and breast cancer. The paper also examines the hybrid approach that increases the performance o