Detailed comparative analysis of diabetes mellitus prediction using machine learning models Online publication date: Wed, 03-Jan-2024
by Arshiya Begum; Sreenivasa Reddy
International Journal of Knowledge Engineering and Data Mining (IJKEDM), Vol. 8, No. 1, 2023
Abstract: Today, millions of people are suffering from diabetes which contributes to many other lethal diseases i.e., heart, kidney, and nerve damage. Diabetes mellitus is a chronic disease characterised by the body's inability to metabolise glucose, which could be life-threatening. Thus, several researchers have attempted to construct an accurate diabetes predictive model over the years. Big data analytics has played a vital role in healthcare by building predictive models for diabetes mellitus using various machine learning techniques. A large amount of data is collected which opened the opportunity to develop more complex, accurate predictions of the model. This paper aims to discuss various machine learning models to predict diabetes mellitus more accurately over the years. We have conducted a thorough review of the literature on predicting diabetes using PIMA and other datasets, which demonstrates how various machine-learning algorithms can be used to predict diabetes.
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Knowledge Engineering and Data Mining (IJKEDM):
Login with your Inderscience username and password:
Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.
If you still need assistance, please email subs@inderscience.com
Our Blog 
Follow us on Twitter 
Visit us on Facebook