Access the full text.
Sign up today, get DeepDyve free for 14 days.
References for this paper are not available at this time. We will be adding them shortly, thank you for your patience.
Machine learning (ML) and data mining (DM) techniques have grown in popularity among researchers and scientists in various fields. The healthcare industry could not be an exception to it. Diabetes or diabetes mellitus, a gaggle of metabolic disorder, can be caused due to age, obesity, lack of exercise, hereditary diabetes, living style, bad diet, hypertension, etc. and for that, the entire body system can be affected harmfully and be susceptible to dangerous diseases like heart disease, kidney disease, stroke, eye problem, nerve damage, etc. For this, we tried to go for a systematic review on diabetes by applying ML and DM classification algorithms for prediction and diagnosis. Concerning the sort of knowledge, medical datasets as well as Pima Indian Diabetes Datasets (PIDDs) provided by the UCI-ML Repository were mainly used. This survey may be useful for further investigation in predictions and resulting valuable knowledge on diabetes.
International Journal of Biomedical Engineering and Technology – Inderscience Publishers
Published: Jan 1, 2023
Read and print from thousands of top scholarly journals.
Already have an account? Log in
Bookmark this article. You can see your Bookmarks on your DeepDyve Library.
To save an article, log in first, or sign up for a DeepDyve account if you don’t already have one.
Copy and paste the desired citation format or use the link below to download a file formatted for EndNote
Access the full text.
Sign up today, get DeepDyve free for 14 days.
All DeepDyve websites use cookies to improve your online experience. They were placed on your computer when you launched this website. You can change your cookie settings through your browser.