Diabetes mellitus risk prediction in the presence of class imbalance using flexible machine learning methods.

Journal: BMC medical informatics and decision making
Published Date: Feb 10, 2022

Abstract

BACKGROUND: Early detection and prediction of type two diabetes mellitus incidence by baseline measurements could reduce associated complications in the future. The low incidence rate of diabetes in comparison with non-diabetes makes accurate prediction of minority diabetes class more challenging.

Authors

  • Somayeh Sadeghi
    Department of Epidemiology and Biostatistics, School of Public Health, Tehran University of Medical Sciences, P.O. Box 14155-6446, Tehran, Iran.
  • Davood Khalili
    Prevention of Metabolic Disorders Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran (AR, FH, DK)
  • Azra Ramezankhani
    Prevention of Metabolic Disorders Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran (AR, FH, DK)
  • Mohammad Ali Mansournia
    Department of Epidemiology and Biostatistics, School of Public Health, Tehran University of Medical Sciences, P.O. Box 14155-6446, Tehran, Iran. mansournia_ma@yahoo.com.
  • Mahboubeh Parsaeian
    Department of Epidemiology and Biostatistics, School of Public Health, Tehran University of Medical Sciences, P.O. Box 14155-6446, Tehran, Iran. mahbobehparsaeian@yahoo.com.

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