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Diagnosis of Type 2 Diabetes and Pre-diabetes Using Machine Learning

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VIII Latin American Conference on Biomedical Engineering and XLII National Conference on Biomedical Engineering (CLAIB 2019)

Part of the book series: IFMBE Proceedings ((IFMBE,volume 75))

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Abstract

The type-2 diabetes (T2D) is a multifactorial chronic disease that reduces the quality of lifestyle and produces the death of a large percentage of the population worldwide. Before the development of T2D a series of symptoms are presented even years before T2D diagnosis. This condition that appears before the development of T2D is called prediabetes. Prediabetes and T2D are diagnosed from the oral glucose tolerance test (OGTT). The OGTT consists in the measurement of glucose and insulin in five-time intervals, the first after 8 h of fasting (0 min) and the other four measurements after taking 75 g of oral glucose in 30-minutes intervals (30, 60, 90 and 120 min). Some parameters have been used to improve the efficiency in the diagnosis of prediabetes and T2D, for example: the area under the glucose (AUCG) and insulin (AUCI) curve during OGTT has been used as a parameter for the diagnosis of prediabetes, T2D and obesity. The aim of this study is to assess the k-means clustering algorithm in the classification of subjects with prediabetes and T2D using the AUCG and AUCI. A database of 188 subjects (male = 88 subjects, age = 42.11 ± 14.91 years old) with values of plasma glucose and insulin during OGTT was used. The k-means clustering performed for AUCG presents acceptable results since the silhouette coefficient is above 0.6 in all cases. The findings in this study indicate that the k-means applied in the AUCG classify subjects with T2D, prediabetes and control. Furthermore, it could even predict those subjects with high probabilities of developing T2D.

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Acknowledgments

This work was funded by the Research Vice-rectorate of the University Antonio Nariño, and the Research and Development Deanery of the Simón Bolívar University (DID) and Pontifical Bolivarian University.

Author information

Authors and Affiliations

  1. Departamento de Termodinámica y Transferencia de Calor, Universidad Simón Bolívar, Caracas, Venezuela

    Erika Severeyn & Jesús Velásquez

  2. Departamento de Electrónica y Circuitos, Universidad Simón Bolívar, Caracas, Venezuela

    Sara Wong

  3. Faculty of Electronic and Biomedical Engineering, Antonio Nariño University, Cartagena, Colombia

    Gilberto Perpiñán

  4. Departamento de Tecnología de Procesos Biológicos y Bioquímicos, Universidad Simón Bolívar, Caracas, Venezuela

    Héctor Herrera

  5. Faculty of Electrical and Electronic Engineering, Pontifical Bolivarian University, Bucaramanga, Colombia

    Miguel Altuve

  6. Departamento de Ingeniería Eléctrica y Computación, Universidad Autónoma de Ciudad Juarez, Ciudad Juarez, Mexico

    José Díaz

Authors
  1. Erika Severeyn
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  2. Sara Wong
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  3. Jesús Velásquez
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  4. Gilberto Perpiñán
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  5. Héctor Herrera
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  6. Miguel Altuve
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  7. José Díaz
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Corresponding author

Correspondence to Erika Severeyn .

Editor information

Editors and Affiliations

  1. Instituto Politécnico Nacional, Mexico City, Mexico

    César A. González Díaz

  2. Departamento de Ingeniería Electrica y Computación, Universidad Autónoma de Ciudad Juárez, Chihuahua, Mexico

    Christian Chapa González

  3. Universidad Nacional de San Juan, San Juan, Argentina

    Eric Laciar Leber

  4. Universidad de Guadalajara, Guadalajara, Mexico

    Hugo A. Vélez

  5. Universidad Autónoma de Nuevo León, Nuevo León, Mexico

    Norma P. Puente

  6. Universidad Autónoma de Baja California, Ensenada, Baja California, Mexico

    Dora-Luz Flores

  7. Universidade Federal de Uberlândia, Uberlândia, Brazil

    Adriano O. Andrade

  8. Instituto Nacional de Cancerología, Mexico City, Mexico

    Héctor A. Galván

  9. Universidad Autónoma Metropolitana, Mexico City, Mexico

    Fabiola Martínez

  10. Universidad Federal de Santa Catarina, Florianópolis, Brazil

    Renato García

  11. Instituto Nacional de Rehabilitación, Mexico City, Mexico

    Citlalli J. Trujillo

  12. Universidad Autónoma de San Luis Potos, San Luis, Mexico

    Aldo R. Mejía

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Severeyn, E. et al. (2020). Diagnosis of Type 2 Diabetes and Pre-diabetes Using Machine Learning. In: González Díaz, C., et al. VIII Latin American Conference on Biomedical Engineering and XLII National Conference on Biomedical Engineering. CLAIB 2019. IFMBE Proceedings, vol 75. Springer, Cham. https://doi.org/10.1007/978-3-030-30648-9_105

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  • DOI: https://doi.org/10.1007/978-3-030-30648-9_105

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-30647-2

  • Online ISBN: 978-3-030-30648-9

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