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

Journals

  1. Peeks F, Hoogeveen I, Feldbrugge R, Burghard R, Boer F, Fokkert‐Wilts M, 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 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