An Intelligent Gestational Diabetes Mellitus Recognition System Using Machine Learning Algorithms

Abstract

Diabetes mellitus is also called gestational diabetes when a woman has high blood sugar while she is pregnant. It can show up at any time during pregnancy and cause problems for the mother and baby during or after the pregnancy. If the risks are found and dealt with as soon as possible, there is a chance that they can be reduced. The healthcare system is one of the many parts of our daily lives that are being rethought thanks to the creation of intelligent systems by machine learning algorithms. In this article, a hybrid prediction model is suggested as a way to find out if a woman has gestational diabetes. In the recommended model, the amount of data is reduce by using the K-means clustering method. Predictions are made using a number of classification methods, such as decision tree, random forests, SVM, KNN, logistic regression, and naive bayes. The results show that accuracy goes up when clustering and classification are used together.