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

mHealth for Symptom and Disease Monitoring, Chronic Disease Management (1301) Artificial Intelligence (1186) Mobile Health (mhealth) (2748) Machine Learning (1370) Apps, Mobile, Wearables for Diabetes (288) Glucose Tracking and Self-Monitoring of Blood Glucose (150) Sensors for Glucose Monitoring and Diabetes Management (29)
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 (44) Tweetations (1) Metrics

Journals

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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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Books/Policy Documents

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