Published on in Vol 8 (2023)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/47592, first published .
An “All-Data-on-Hand” Deep Learning Model to Predict Hospitalization for Diabetic Ketoacidosis in Youth With Type 1 Diabetes: Development and Validation Study

An “All-Data-on-Hand” Deep Learning Model to Predict Hospitalization for Diabetic Ketoacidosis in Youth With Type 1 Diabetes: Development and Validation Study

An “All-Data-on-Hand” Deep Learning Model to Predict Hospitalization for Diabetic Ketoacidosis in Youth With Type 1 Diabetes: Development and Validation Study

Journals

  1. Ebekozien O, Mungmode A, Sanchez J, Rompicherla S, Demeterco-Berggren C, Weinstock R, Jacobsen L, Davis G, McKee A, Akturk H, Maahs D, Kamboj M. Longitudinal Trends in Glycemic Outcomes and Technology Use for Over 48,000 People with Type 1 Diabetes (2016–2022) from the T1D Exchange Quality Improvement Collaborative. Diabetes Technology & Therapeutics 2023;25(11):765 View
  2. Obaido G, Ogbuokiri B, Chukwu C, Osaye F, Egbelowo O, Uzochukwu M, Mienye I, Aruleba K, Primus M, Achilonu O. An Improved Ensemble Method for Predicting Hyperchloremia in Adults With Diabetic Ketoacidosis. IEEE Access 2024;12:9536 View
  3. Teixeira P, Battelino T, Carlsson A, Gudbjörnsdottir S, Hannelius U, von Herrath M, Knip M, Korsgren O, Elding Larsson H, Lindqvist A, Ludvigsson J, Lundgren M, Nowak C, Pettersson P, Pociot F, Sundberg F, Åkesson K, Lernmark Å, Forsander G. Assisting the implementation of screening for type 1 diabetes by using artificial intelligence on publicly available data. Diabetologia 2024;67(6):985 View
  4. Nimri R, Phillip M, Clements M, Kovatchev B. Closed-Loop Control, Artificial Intelligence–Based Decision-Support Systems, and Data Science. Diabetes Technology & Therapeutics 2024;26(S1):S-68 View
  5. El Emam K, Leung T, Malin B, Klement W, Eysenbach G. Consolidated Reporting Guidelines for Prognostic and Diagnostic Machine Learning Models (CREMLS). Journal of Medical Internet Research 2024;26:e52508 View