Abstract
Techniques of machine learning are used in a large amount of sectors and contribution in developing it. The ML plays the vital role in the medical field in reducing the risk of chronic diseases by prediction of disease before occurring with the help of the internet of things technique. The diabetes is the most disease leading to death in this time that destroys the human life especially of elderly people. In this work, we focus on gestational diabetes which a large number of woman get during pregnancy that increases the risk on the fetuses. We will use the raw dataset from the Kaggle (Pima Indian Diabetes Data Set) which contains 769 instances and 8 attributes. In our project, we used the most classification algorithms of ML for prediction of diabetics (k-NN, DT, NP, RF, SVM, logistic regression, XGBoost, CATBoost, and NN). We got the high accuracy compared by some previous researchers in the same disease.
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Bhagile, V.D., Fathail, I. (2022). Gestational Diabetes Prediction Using Machine Learning Algorithms. In: Poonia, R.C., Singh, V., Singh Jat, D., Diván, M.J., Khan, M.S. (eds) Proceedings of Third International Conference on Sustainable Computing. Advances in Intelligent Systems and Computing, vol 1404. Springer, Singapore. https://doi.org/10.1007/978-981-16-4538-9_6
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DOI: https://doi.org/10.1007/978-981-16-4538-9_6
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