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

Apps, Mobile, Wearables for Diabetes (306) Artificial Intelligence (1421) Machine Learning (1501) mHealth for Symptom and Disease Monitoring, Chronic Disease Management (1428) Apps, Mobile, Wearables for Diabetes (306) Glucose Tracking and Self-Monitoring of Blood Glucose (166)

Published on in Vol 5, No 3 (2020): Jul-Sep

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/18660, first published .
The Diabits App for Smartphone-Assisted Predictive Monitoring of Glycemia in Patients With Diabetes: Retrospective Observational Study

The Diabits App for Smartphone-Assisted Predictive Monitoring of Glycemia in Patients With Diabetes: Retrospective Observational Study

The Diabits App for Smartphone-Assisted Predictive Monitoring of Glycemia in Patients With Diabetes: Retrospective Observational Study

Authors of this article:

Stan Kriventsov1 Author Orcid Image ;   Alexander Lindsey1 Author Orcid Image ;   Amir Hayeri1 Author Orcid Image
Article Authors Cited by (14) Tweetations (64) Metrics

Journals

  1. Peeks F, Hoogeveen I, Feldbrugge R, Burghard R, de Boer F, Fokkert‐Wilts M, van der Klauw M, Oosterveer M, Derks T. A retrospective in‐depth analysis of continuous glucose monitoring datasets for patients with hepatic glycogen storage disease: Recommended outcome parameters for glucose management. Journal of Inherited Metabolic Disease 2021;44(5):1136 View
  2. Garzorz-Stark N, Beicht S, Baghin V, Stark S, Biedermann T, Lauffer F. IMPROVE 1.0: Individual Monitoring of Psoriasis Activity by Regular Online App Questionnaires and Outpatient Visits. Frontiers in Medicine 2021;8 View
  3. 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
  4. Felizardo V, Machado D, Garcia N, Pombo N, Brandao P. Hypoglycaemia Prediction Models With Auto Explanation. IEEE Access 2022;10:57930 View
  5. Klemme I, Wrona K, de Jong I, Dockweiler C, Aschentrup L, Albrecht J. Integration of the Vision of People With Diabetes Into the Development Process to Improve Self-management via Diabetes Apps: Qualitative Interview Study. JMIR Diabetes 2023;8:e38474 View
  6. Rossi A, Venema A, Haarsma P, Feldbrugge L, Burghard R, Rodriguez-Buritica D, Parenti G, Oosterveer M, Derks T. A Prospective Study on Continuous Glucose Monitoring in Glycogen Storage Disease Type Ia: Toward Glycemic Targets. The Journal of Clinical Endocrinology & Metabolism 2022;107(9):e3612 View
  7. Zhou Y, Gould D, Choong P, Dowsey M, Schilling C. Implementing predictive tools in surgery: A narrative review in the context of orthopaedic surgery. ANZ Journal of Surgery 2022;92(12):3162 View
  8. PALAZ Z, DOĞAN V, KILIÇ V. Smartphone-based Multi-parametric Glucose Prediction using Recurrent Neural Networks. European Journal of Science and Technology 2022 View
  9. Afsaneh E, Sharifdini A, Ghazzaghi H, Ghobadi M. Recent applications of machine learning and deep learning models in the prediction, diagnosis, and management of diabetes: a comprehensive review. Diabetology & Metabolic Syndrome 2022;14(1) View
  10. Wolff M, Schaathun H, Fougner A, Steinert M, Volden R. Mobile Software Development Kit for Real Time Multivariate Blood Glucose Prediction. IEEE Access 2024;12:5910 View
  11. Zhu T, Kuang L, Piao C, Zeng J, Li K, Georgiou P. Population-Specific Glucose Prediction in Diabetes Care With Transformer-Based Deep Learning on the Edge. IEEE Transactions on Biomedical Circuits and Systems 2024;18(2):236 View
  12. Lubasinski N, Thabit H, Nutter P, Harper S. Blood Glucose Prediction from Nutrition Analytics in Type 1 Diabetes: A Review. Nutrients 2024;16(14):2214 View
  13. Herrero P, Andorrà M, Babion N, Bos H, Koehler M, Klopfenstein Y, Leppäaho E, Lustenberger P, Peak A, Ringemann C, Glatzer T. Enhancing the Capabilities of Continuous Glucose Monitoring With a Predictive App. Journal of Diabetes Science and Technology 2024;18(5):1014 View