Automatic Diagnosis of Diabetes Using Machine Learning: A Review

Authors

  • Takudzwa Fadziso Chinhoyi University of Technology
  • Harshini Priya Adusumalli iMinds Technology systems, Inc.

DOI:

https://doi.org/10.18034/mjmbr.v7i2.555

Keywords:

Machine Learning, Diabetes, Diabetes Detection, Blood Sugar

Abstract

The health sector, like the other sectors, contains a large amount of data that should be used to better understand and treat the various ailments that are prevalent. For example, diabetes is a condition that is becoming more prevalent but that may be managed if discovered at an early stage. The algorithms of machine learning (ML) can be utilized for this purpose. We have examined the various machine learning methods and the attributes that can be utilized to train these algorithms for the purpose of detecting diabetic complications.

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Author Biographies

  • Takudzwa Fadziso, Chinhoyi University of Technology

    Institute of Lifelong Learning and Development Studies, Chinhoyi University of Technology, ZIMBABWE

  • Harshini Priya Adusumalli, iMinds Technology systems, Inc.

    Software Developer, iMinds Technology systems, Inc., 1145 Bower Hill Rd, Pittsburgh, PA, USA

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Published

2020-11-01

Issue

Section

Peer-reviewed Article

How to Cite

Fadziso, T., & Adusumalli, H. P. (2020). Automatic Diagnosis of Diabetes Using Machine Learning: A Review. Malaysian Journal of Medical and Biological Research, 7(2), 129-134. https://doi.org/10.18034/mjmbr.v7i2.555