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The Prevalence of Diabetes in the Republic of Kazakhstan Based on Regression Analysis Methods

Author

Listed:
  • A. Mukasheva

    (Department of Cybersecurity, Data Processing and Storage, Satbayev University, Almaty, Kazakhstan)

  • N. Saparkhojayev

    (Khoja Akhmet Yassawi International Kazakh-Turkish University, Turkestan, Kazakhstan)

  • Z. Akanov

    (Kazakh Society for Study of Diabetes, Member of AASD, Almaty, Kazakhstan)

  • A. Algazieva

    (Academy of Civil Aviation, Almaty, Kazakhstan)

Abstract

In this research paper, experimental studies of regression analysis methods for predicting diabetes mellitus of patients for 2019 in the Republic of Kazakhstan were conducted. Linear, polynomial, and exponential regressions methods were considered, after which appropriate graphs were built. According to these results it can be seen that the growth of development of patients with diabetes mellitus will not decrease. This is another confirmation that researchers need to apply new modern information technologies based on machine learning and artificial intelligence to struggle with the growth of this disease.

Suggested Citation

  • A. Mukasheva & N. Saparkhojayev & Z. Akanov & A. Algazieva, 2019. "The Prevalence of Diabetes in the Republic of Kazakhstan Based on Regression Analysis Methods," International Journal of Health and Medical Sciences, Mohammad A. H. Khan, vol. 5(1), pages 8-16.
    • Handle: RePEc:apa:ijhmss:2019:p:8-16
    DOI: 10.20469/ijhms.5.30002-1
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    References listed on IDEAS

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    1. Kantapong Prabsangob, 2016. "Relationships of Health Literacy Diabetes Knowledge and Social Support to Self-Care Behavior among Type 2 Diabetic Patients," International Journal of Health and Medical Sciences, Mohammad A. H. Khan, vol. 2(3), pages 68-72.
    2. Thipapan Sungkhapong & Poosadee Prommete & Namthip Martkoksoong & Boonsri Kittichottipanich, 2016. "The health behaviors’ modification for controlling and prevention of diabetes mellitus by using promise model at premruthai pravate community Bangkok," Journal of Advances in Health and Medical Sciences, Balachandar S. Sayapathi, vol. 2(3), pages 97-101.
    3. Amal Malehi & Fatemeh Pourmotahari & Kambiz Angali, 2015. "Statistical models for the analysis of skewed healthcare cost data: a simulation study," Health Economics Review, Springer, vol. 5(1), pages 1-16, December.
    4. R. Rizal Isnanto & Dania Eridani & Sri S.Y. Wulandari Simbolon, 2018. "Expert System for Diabetes Mellitus Detection and Handling Using Certainty Factor on Android-Based Mobile Device," International Journal of Health and Medical Sciences, Mohammad A. H. Khan, vol. 4(2), pages 28-39.
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