A stacked ensemble machine learning approach for the prediction of diabetes.

Journal: Journal of diabetes and metabolic disorders
Published Date: Nov 22, 2023

Abstract

OBJECTIVES: Diabetes has become a leading cause of mortality in both developed and developing countries, impacting a growing number of individuals worldwide. As the prevalence of the disease continues to rise, researchers have diligently worked towards developing accurate diabetes prediction models. The primary aim of this study is to utilize a diverse set of machine learning algorithms to detect the presence of diabetes, particularly in females, at an early stage. By leveraging these methods, this research seeks to provide physicians with valuable tools to identify the disease early, enabling timely interventions and improving patient outcomes.

Authors

  • Khondokar Oliullah
    Department of Computer Science and Engineering, Bangladesh University of Business and Technology, Dhaka, Bangladesh.
  • Mahedi Hasan Rasel
    Department of Computer Science and Engineering, Bangladesh University of Business and Technology, Dhaka, Bangladesh.
  • Md Manzurul Islam
    Department of Computer Science and Engineering, Bangladesh University of Business and Technology, Dhaka, Bangladesh.
  • Md Reazul Islam
    Department of Computer Science and Engineering, Bangladesh University of Business and Technology, Dhaka, Bangladesh.
  • Md Anwar Hussen Wadud
    Department of Computer Science and Engineering, Bangladesh University of Business and Technology, Dhaka, Bangladesh.
  • Md Whaiduzzaman
    School of Information Systems, Queensland University of Technology, Brisbane, Australia.

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