Machine Learning Methods for prediction of Diabetes: A Narrative Review

One of the challenging issues while creating medical diagnosis software is reportedly disease prediction. Numerous applications, including medical diagnosis, have effectively used machine learning techniques. Machine learning algorithms may greatly assist in resolving health-related problems by creating classifier systems, which can help doctors forecast and detect diseases early. We can improve the present system's speed, performance, reliability, and accuracy in identifying a certain disease using machine learning classification methods. The review of diabetic disease diagnosis using machine learning approaches is the focus of this research. Additionally, this study summarizes diabetic diagnosis using machine learning algorithms. The primary goals of the evaluated publications are a reliable diagnosis and classification.

کلیدواژه ها:

_ Machine Learning ، Diabetes ، Detection ، Features extracted ، Artificial neural networks