Predicting complications of diabetes mellitus using advanced machine learning algorithms.

Journal: Journal of the American Medical Informatics Association : JAMIA
Published Date: Jul 1, 2020

Abstract

OBJECTIVE: We sought to predict if patients with type 2 diabetes mellitus (DM2) would develop 10 selected complications. Accurate prediction of complications could help with more targeted measures that would prevent or slow down their development.

Authors

  • Branimir Ljubic
    Center for Data Analytics and Biomedical Informatics, Temple University, Philadelphia, Pennsylvania, USA.
  • Ameen Abdel Hai
    Center for Data Analytics and Biomedical Informatics, Temple University, Philadelphia, Pennsylvania, USA.
  • Marija Stanojevic
    Center for Data Analytics and Biomedical Informatics, Temple University, Philadelphia, Pennsylvania, USA.
  • Wilson Diaz
    Center for Data Analytics and Biomedical Informatics, Temple University, Philadelphia, Pennsylvania, USA.
  • Daniel Polimac
    Center for Data Analytics and Biomedical Informatics, Temple University, Philadelphia, Pennsylvania, USA.
  • Martin Pavlovski
    Macedonian Academy of Sciences and Arts, Research Center for Computer Science and Information Technologies, Skopje, 1000, Republic of Macedonia.
  • Zoran Obradovic

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