Diabetes detection using deep learning techniques with oversampling and feature augmentation.

Journal: Computer methods and programs in biomedicine
Published Date: Feb 15, 2021

Abstract

BACKGROUND AND OBJECTIVE: Diabetes is a chronic pathology which is affecting more and more people over the years. It gives rise to a large number of deaths each year. Furthermore, many people living with the disease do not realize the seriousness of their health status early enough. Late diagnosis brings about numerous health problems and a large number of deaths each year so the development of methods for the early diagnosis of this pathology is essential.

Authors

  • Maria Teresa García-Ordás
    Department of Electrical, Systems and Automatic Engineering, Universidad of León, Campus de Vegazana s/n, León 24071, Spain. Electronic address: mgaro@unileon.es.
  • Carmen Benavides
    Department of Electric, Systems and Automatic Engineering, SALBIS Research Group, University of Leon, León 24007, Spain.
  • José Alberto Benítez-Andrades
    SALBIS Research Group, Department of Electric, Systems and Automatics Engineering, University of León, Campus of Vegazana s/n, 24071 León, Spain.
  • Héctor Alaiz-Moretón
    SECOMUCI Research Groups, Escuela de Ingenierías Industrial e Informática, Universidad de León, Campus de Vegazana s/n, C.P. 24071 León, Spain.
  • Isaías García-Rodríguez
    SECOMUCI Research Groups, Escuela de Ingenierías Industrial e Informática, Universidad de León, Campus de Vegazana s/n, C.P. 24071 León, Spain.

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