Early Gestational Diabetes Mellitus Diagnosis Using Classification Algorithms: An Ensemble Approach-Reference-Cited by-同舟云学术

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Early Gestational Diabetes Mellitus Diagnosis Using Classification Algorithms: An Ensemble Approach

Published:2023-09-20 Issue: Volume: Page:
ISSN:
Container-title:2023 IEEE AFRICON
language:
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Author:

Abe Oluwafemi O.S.¹,Obe Olumide O.¹,Boyinbode Olutayo K.²,Olagbuji N. Biodun³

Affiliation:

1. The Federal University of Technology,Department of Computer Science,Akure,Nigeria

2. The Federal University of Technology,Department of Information Technology,Akure,Nigeria

3. Ekiti State University,Department of Obstetrics and Gynecology,Ado-Ekiti,Nigeria

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10293181/10293212/10293603.pdf?arnumber=10293603

Reference26 articles.

1. Ensemble Classifier Technique to Predict Gestational Diabetes Mellitus (GDM)

2. Prediction of gestational diabetes based on nationwide electronic health records

3. Predicting Hypoglycemia In Diabetic Patients Using Machine Learning Techniques;khouloud-abdel aziz safi;Faculty of the American University of Sharjah,2014

4. Comparative Analysis of Predictive Models for Diagnosis of Lower Respiratory Infections among Paediatric patients;olayemi;Computer Review,2020

5. Comparison of Machine Learning Methods and Conventional Logistic Regressions for Predicting Gestational Diabetes Using Routine Clinical Data: A Retrospective Cohort Study;ye;Diabetes Research,2020

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