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

Diabetes Self-Management (630) mHealth for Symptom and Disease Monitoring, Chronic Disease Management (1829) mHealth for Telemedicine and Homecare (571) Glucose Tracking and Self-Monitoring of Blood Glucose (208) Apps, Mobile, Wearables for Diabetes (380) Telemedicine for Diabetes (122)

Published on in Vol 8 (2023)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/44277, first published .
The Effectiveness of an App (Insulia) in Recommending Basal Insulin Doses for French Patients With Type 2 Diabetes Mellitus: Longitudinal Observational Study

The Effectiveness of an App (Insulia) in Recommending Basal Insulin Doses for French Patients With Type 2 Diabetes Mellitus: Longitudinal Observational Study

The Effectiveness of an App (Insulia) in Recommending Basal Insulin Doses for French Patients With Type 2 Diabetes Mellitus: Longitudinal Observational Study

Authors of this article:

Camille Nevoret1 Author Orcid Image ;   Nathalie Gervaise2 Author Orcid Image ;   Brigitte Delemer3 Author Orcid Image ;   Said Bekka4 Author Orcid Image ;   Bruno Detournay1 Author Orcid Image ;   Amine Benkhelil5 Author Orcid Image ;   Amar Bahloul5 Author Orcid Image ;   Geneviève d'Orsay6 Author Orcid Image ;   Alfred Penfornis7 Author Orcid Image
Article Authors Cited by (7) Tweetations (5) Metrics

Journals

  1. Luo E, Wan J, Su M, Wang J, Feng J, Xie X, Hong X. Efficacy of a basal insulin dose management smartphone application for controlling fasting blood glucose in patients with type‐2 diabetes mellitus: A single‐centre, randomised clinical study. Clinical Endocrinology 2023;99(4):361 View
  2. Vangoitsenhoven R, Van der Schueren B. Basal insulin titration by the app. The Lancet Regional Health - Europe 2023;33:100720 View
  3. Thomsen C, Kronborg T, Hangaard S, Vestergaard P, Hejlesen O, Jensen M. Modeling the fasting blood glucose response to basal insulin adjustment in type 2 diabetes: An explainable machine learning approach on real-world data. International Journal of Medical Informatics 2025;195:105758 View
  4. Carlson A, Badlani S, Shah V. The Role, Potential Benefits and Cost-effectiveness of Digital Tools for Diabetes Management. Clinical Therapeutics 2025;47(8):638 View
  5. Nimri R, Phillip M. Enhancing Care in Type 1 Diabetes with Artificial Intelligence Driven Clinical Decision Support Systems. Hormone Research in Paediatrics 2025;98(4):384 View
  6. Sung J, Midorikawa-Inomata A, Fujio K, Inomata T. Expanding the horizon of oculomics: A narrative review on the emerging roles of the anterior segment and mobile health. Survey of Ophthalmology 2026 View
  7. Ory M, Esquivel C, Han G, Towne Jr S, Ahn S, Smith M. Personalized Digital Health Solutions to Increasing Diabetes-Related Knowledge and Behavioral Outcomes: Results from an RCT  (Preprint). JMIR Diabetes 2025 View