Automated detection and classification of diabetes disease based on Bangladesh demographic and health survey data, 2011 using machine learning approach.

Journal: Diabetes & metabolic syndrome

PMID: 32193086

Abstract

BACKGROUND AND AIMS: Diabetes has been recognized as a continuing health challenge for the twenty-first century, both in developed and developing countries including Bangladesh. The main objective of this study is to use machine learning (ML) based classifiers for automated detection and classification of diabetes.

Authors

Md Merajul Islam

Department of Statistics, University of Rajshahi, Rajshahi, 6205, Bangladesh. Electronic address: merajul.stat4811@gmail.com.
Md Jahanur Rahman

Department of Statistics, University of Rajshahi, Rajshahi, Bangladesh.
Dulal Chandra Roy

Department of Statistics, University of Rajshahi, Rajshahi, 6205, Bangladesh. Electronic address: dulalroystat@yahoo.com.
Md Maniruzzaman

Department of Statistics, University of Rajshahi, Rajshahi, Bangladesh. Electronic address: monir.stat91@gmail.com.

Keywords

Adult Area Under Curve Automation Bangladesh Demography Diabetes Mellitus Diabetes Mellitus, Type 2 Discriminant Analysis Factor Analysis, Statistical Female Health Surveys Humans Logistic Models Machine Learning Male Middle Aged Reproducibility of Results Support Vector Machine Treatment Outcome

External Resources

View on PubMed Access via DOI PubMed (32193086)

Automated detection and classification of diabetes disease based on Bangladesh demographic and health survey data, 2011 using machine learning approach.

Abstract

Authors

Keywords

External Resources

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