Machine Learning-Based Application for Predicting Risk of Type 2 Diabetes Mellitus (T2DM) in Saudi Arabia: A Retrospective Cross-Sectional Study

Earlier detection of individuals at the highest risk of developing diabetes is crucial to avoid the disease's prevalence and progression. Therefore, we aim to build a data-driven predictive application for screening subjects at a high risk of developing Type 2 Diabetes mellitus (T2DM) in the we...

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Bibliographic Details
Published in:	IEEE access Vol. 8; pp. 199539 - 199561
Main Authors:	Syed, Asif Hassan, Khan, Tabrej
Format:	Journal Article
Language:	English
Published:	Piscataway IEEE 2020 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:	Adaptation models Algorithms Application Body size Chi-square test Cross-sectional studies cross-sectional study Datasets Diabetes Diabetes mellitus Forestry Indexes Logistics Machine learning Nutrition predictive model Predictive models Regression analysis Risk analysis statistical techniques/model Statistical tests type 2 diabetes mellitus (T2DM) Web services Saudi Arabia
ISSN:	2169-3536, 2169-3536
Online Access:	Get full text
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