A Review: Application of Machine Learning Algorithm in Medical Diagnosis

Abstract

After Covid 19 Pandemic people are more focusing on healthcare. Every person wants to get the solution related to any health issue from their doorstep, this is the reason that Machine learning techniques has been adopted very fast in the field of medical diagnosis which can provide fast and accurate diagnosis results at the time of disease diagnosis step this system will assist physician to predict the diseases in early stage. Using Machine learning the correct diagnosis can be done when the system will get the complete, sufficient and proper information with respect to the problem. Because of if the system will not get the proper information related to the disease this will leads to some diagnostic error by this adverse impact on the treatment of the patient. Machine learning works upon the concept of train and test the machine with the required algorithm which can provide efficient result for execution of this process first we need to train the machine with respect to the data collected and after collecting the data, data cleaning processing to be done efficiently so that we get the correct feature extraction when we follow the test step. In this research paper we are presenting comparative analysis of various machine learning algorithm ie. Linear regression. Decision tree, SVM, Random Forest etc. Applied in the field of medical diagnosis our analysis in focusing on the criteria with respect to the accuracy, performance and algorithm is applied for medical diagnosis.