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A Machine Learning Web App to Predict Diabetic Blood Glucose Based on a Basic Noninvasive Health Checkup, Sociodemographic Characteristics, and Dietary Information: Case Study.

Masuda Begum SampaTopu BiswasMd Siddikur RahmanNor Hidayati Binti Abdul AzizMd Nazmul HossainNor Azlina Ab Aziz
Published in: JMIR diabetes (2023)
This ML-enabled web application for blood glucose prediction helps individuals to self-monitor their health condition. The application was developed with communities in remote areas of low- and middle-income countries, such as Bangladesh, in mind. These areas typically lack health facilities and have an insufficient number of qualified doctors and nurses. The web-based application is a simple, practical, and effective solution that can be adopted by the community. Use of the web application can save money on medical expenses, time, and health management expenses. The created system also aids in achieving the Sustainable Development Goals, particularly in ensuring that everyone in the community enjoys good health and well-being and lowering total morbidity and mortality.
Keyphrases
  • healthcare
  • blood glucose
  • mental health
  • public health
  • machine learning
  • health information
  • type diabetes
  • human health
  • blood pressure
  • glycemic control
  • skeletal muscle
  • big data
  • insulin resistance
  • deep learning