This paper is in the following e-collection/theme issue:

mHealth for Symptom and Disease Monitoring, Chronic Disease Management (1399) Artificial Intelligence (1371) Mobile Health (mhealth) (2939) Machine Learning (1465) Apps, Mobile, Wearables for Diabetes (298) Glucose Tracking and Self-Monitoring of Blood Glucose (162) Sensors for Glucose Monitoring and Diabetes Management (33)
Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/14452, first published .
Development of a Deep Learning Model for Dynamic Forecasting of Blood Glucose Level for Type 2 Diabetes Mellitus: Secondary Analysis of a Randomized Controlled Trial

Development of a Deep Learning Model for Dynamic Forecasting of Blood Glucose Level for Type 2 Diabetes Mellitus: Secondary Analysis of a Randomized Controlled Trial

Development of a Deep Learning Model for Dynamic Forecasting of Blood Glucose Level for Type 2 Diabetes Mellitus: Secondary Analysis of a Randomized Controlled Trial

Authors of this article:

Syed Hasib Akhter Faruqui1 Author Orcid Image ;   Yan Du2 Author Orcid Image ;   Rajitha Meka1 Author Orcid Image ;   Adel Alaeddini1 Author Orcid Image ;   Chengdong Li2 Author Orcid Image ;   Sara Shirinkam3 Author Orcid Image ;   Jing Wang2 Author Orcid Image
Article Authors Cited by (46) Tweetations (1) Metrics

Journals

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  7. van Doorn W, Foreman Y, Schaper N, Savelberg H, Koster A, van der Kallen C, Wesselius A, Schram M, Henry R, Dagnelie P, de Galan B, Bekers O, Stehouwer C, Meex S, Brouwers M, Chen C. Machine learning-based glucose prediction with use of continuous glucose and physical activity monitoring data: The Maastricht Study. PLOS ONE 2021;16(6):e0253125 View
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  14. Fowers R, Berardi V, Huberty J, Stecher C. Using mobile meditation app data to predict future app engagement: an observational study. Journal of the American Medical Informatics Association 2022;29(12):2057 View
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  20. Triantafyllidis A, Kondylakis H, Katehakis D, Kouroubali A, Koumakis L, Marias K, Alexiadis A, Votis K, Tzovaras D. Deep Learning in mHealth for Cardiovascular Disease, Diabetes, and Cancer: Systematic Review. JMIR mHealth and uHealth 2022;10(4):e32344 View
  21. Kim H, Hwang S, Lee S, Kim Y. Classification and Prediction on Hypertension with Blood Pressure Determinants in a Deep Learning Algorithm. International Journal of Environmental Research and Public Health 2022;19(22):15301 View
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Books/Policy Documents

  1. Malhotra S, Chhikara R. Intelligent Healthcare. View
  2. Li S, Wang J. Diabetes Digital Health and Telehealth. View