IDEAS home Printed from https://ideas.repec.org/a/igg/joris0/v13y2022i2p1-13.html
   My bibliography  Save this article

A Role of Artificial Intelligence in Healthcare Data for Diabetic People Affected by COVID-19

Author

Listed:
  • Kiran Kumar K.

    (Chalapathi Institute of Engineering and Technology, India)

  • Vijaya Kumar Gudivada

    (Nawab Shah Alam Khan College of Engineering and Technology, India)

  • Panneer Selvam M.

    (Sona College of Technology, India)

  • Bayavanda Chinnappa Thimmaiah

    (Caucasus University, Georgia)

  • Kotaiah Bonthu

    (Maulana Azad National Urdu University, India)

  • R. N. Thakur

    (LBEF Campus, Nepal)

Abstract

Artificial intelligence (AI) enables the diabetic patient's symptoms and biomarkers to be monitored. People with diabetes are weak, and if a COVID-19 infection is present, the patient must be managed optimally, with a focus on fighting the virus while simultaneously maintaining homeostasis and glycemic control. This study examines the present state of knowledge and limitations in using AI to prevent and manage individuals with diabetes and COVID-19 infection. Furthermore, patient engagement in diabetes care is improved by media and online. These innovative technological advancements have improved glycemic management by lowering fasting and by tracking postprandial glucose levels and glycosylated haemoglobin. In this pandemic period, glycemic management and the implementation of suitable interventions are crucial considerations for diabetic patients, particularly those with an active illness. More research is needed in the future to provide care for diabetic patients' psychological and nutritional well-being as well as to reduce their healthcare costs by building focused AI systems.

Suggested Citation

  • Kiran Kumar K. & Vijaya Kumar Gudivada & Panneer Selvam M. & Bayavanda Chinnappa Thimmaiah & Kotaiah Bonthu & R. N. Thakur, 2022. "A Role of Artificial Intelligence in Healthcare Data for Diabetic People Affected by COVID-19," International Journal of Operations Research and Information Systems (IJORIS), IGI Global, vol. 13(2), pages 1-13, August.
    • Handle: RePEc:igg:joris0:v:13:y:2022:i:2:p:1-13
    as

    Download full text from publisher

    File URL: http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/IJORIS.306196
    Download Restriction: no
    ---><---

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:igg:joris0:v:13:y:2022:i:2:p:1-13. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Journal Editor (email available below). General contact details of provider: https://www.igi-global.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.