Research on Diabetes Prediction Based on Machine Learning

Abstract

Diabetes is a serious chronic disease and successful prediction can effectively improve early intervention and subsequent treatment. Nowadays, machine learning technology is gradually attracting people’s attention in diabetes prediction. However, previous research is relatively limited for now. This review systematically and comprehensively reviews the current status of diabetes prediction, the application of machine learning in this field, and the current challenges faced by machine learning. First, the epidemiological characteristics of diabetes and the background of the rise of machine learning in the medical field are introduced. Secondly, the latest progress and typical cases of machine learning technology in diabetes prediction are discussed. Subsequently, the methods and challenges of data collection and feature processing are discussed in detail, as well as commonly used machine learning models and their evaluation methods. We will further comprehensively analyze the main findings and results of existing research, evaluate the application effect of machine learning in diabetes prediction, and look forward to future research directions and development trends. This review will provide researchers with a comprehensive guide to the latest advances and methods of machine learning in diabetes prediction and promote further research and applications in related fields.