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The Prediction of Diabetes

Author

Listed:
  • Massaro, Alessandro
  • Magaletti, Nicola
  • Cosoli, Gabriele
  • Giardinelli, Vito O. M.
  • Leogrande, Angelo
Abstract
The following article presents an analysis of the determinants of diabetes using a dataset containing the surveys of 2000 patients from the Frankfurt Hospital in Germany. The data were analyzed using the following models, namely: Tobit, Probit, Logit, Multinomial Logit, OLS, WLS with heteroskedasticity. The results show that the presence of diabetes is positively associated with "Pregnancies", "Glucose", "BMI", "Diabetes Pedigree Function", "Age" and negatively associated with "Blood Pressure". A cluster analysis is realized using the fuzzy c-Means algorithm optimized with the Elbow method and three clusters were found. Finally a confrontation among eight different machine learning algorithms is realized to select the best performing algorithm to predict the probability of patients to develop diabetes.

Suggested Citation

  • Massaro, Alessandro & Magaletti, Nicola & Cosoli, Gabriele & Giardinelli, Vito O. M. & Leogrande, Angelo, 2022. "The Prediction of Diabetes," MPRA Paper 113372, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:113372
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    File URL: https://mpra.ub.uni-muenchen.de/113372/1/MPRA_paper_113372.pdf
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    References listed on IDEAS

    as
    1. Muhammad Mazhar Bukhari & Bader Fahad Alkhamees & Saddam Hussain & Abdu Gumaei & Adel Assiri & Syed Sajid Ullah & Michela Gelfusa, 2021. "An Improved Artificial Neural Network Model for Effective Diabetes Prediction," Complexity, Hindawi, vol. 2021, pages 1-10, April.
    Full references (including those not matched with items on IDEAS)

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      More about this item

      Keywords

      Machine Learning; Clusterization; Elbow Method; Prediction; Correlation Matrix; Principal Component Analysis; Binary and non-Binary regression models.;
      All these keywords.

      JEL classification:

      • I10 - Health, Education, and Welfare - - Health - - - General
      • I11 - Health, Education, and Welfare - - Health - - - Analysis of Health Care Markets
      • I12 - Health, Education, and Welfare - - Health - - - Health Behavior
      • I13 - Health, Education, and Welfare - - Health - - - Health Insurance, Public and Private
      • I14 - Health, Education, and Welfare - - Health - - - Health and Inequality
      • I15 - Health, Education, and Welfare - - Health - - - Health and Economic Development
      • I18 - Health, Education, and Welfare - - Health - - - Government Policy; Regulation; Public Health

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