A Survey on Medical Diagnosis of Diabetes Using Machine Learning Techniques

While designing medical diagnosis software, disease prediction is said to be one of the captious tasks. The techniques of machine learning have been successfully employed in assorted applications including medical diagnosis. By developing classifier system, machine learning algorithm may immensely help to solve the health-related issues which can assist the physicians to predict and diagnose diseases at an early stage. We can ameliorate the speed, performance, reliability, and accuracy of diagnosing on the current system for a specific disease by using the machine learning classification algorithms. This paper mainly targets the review of diabetes disease detection using the techniques of machine learning. Further, PIMA Indian Diabetic dataset is employed in machine learning techniques like artificial neural networks, decision tree, random forest, naive Bayes, k-nearest neighbors, support vector machines, and logistic regression and discussed the results with their pros and cons.