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

Clinical Information and Decision Making (1407) Machine Learning (1465) Gestational Diabetes (28) Diabetes Prevention (83) Apps, Mobile, Wearables for Diabetes (298) Glucose Tracking and Self-Monitoring of Blood Glucose (162) Decision Support for Health Professionals (1185)

Published on in Vol 23, No 3 (2021): March

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/21435, first published .
Toward a Multivariate Prediction Model of Pharmacological Treatment for Women With Gestational Diabetes Mellitus: Algorithm Development and Validation

Toward a Multivariate Prediction Model of Pharmacological Treatment for Women With Gestational Diabetes Mellitus: Algorithm Development and Validation

Toward a Multivariate Prediction Model of Pharmacological Treatment for Women With Gestational Diabetes Mellitus: Algorithm Development and Validation

Authors of this article:

Carmelo Velardo1, 2 Author Orcid Image ;   David Clifton1, 2 Author Orcid Image ;   Steven Hamblin1 Author Orcid Image ;   Rabia Khan1 Author Orcid Image ;   Lionel Tarassenko1, 2 Author Orcid Image ;   Lucy Mackillop1, 3, 4 Author Orcid Image
Article Authors Cited by (10) Tweetations (5) Metrics

Journals

  1. 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
  2. Gautier T, Ziegler L, Gerber M, Campos-Náñez E, Patek S. Artificial intelligence and diabetes technology: A review. Metabolism 2021;124:154872 View
  3. Huang J, Yeung A, Armstrong D, Battarbee A, Cuadros J, Espinoza J, Kleinberg S, Mathioudakis N, Swerdlow M, Klonoff D. Artificial Intelligence for Predicting and Diagnosing Complications of Diabetes. Journal of Diabetes Science and Technology 2023;17(1):224 View
  4. Imrisek S, Lee M, Goldner D, Nagra H, Lavaysse L, Hoy-Rosas J, Dachis J, Sears L. Effects of a Novel Blood Glucose Forecasting Feature on Glycemic Management and Logging in Adults With Type 2 Diabetes Using One Drop: Retrospective Cohort Study. JMIR Diabetes 2022;7(2):e34624 View
  5. Soldavini C, Piuri G, Rossi G, Corsetto P, Benzoni L, Maggi V, Privitera G, Spadafranca A, Rizzo A, Ferrazzi E. Maternal AA/EPA Ratio and Triglycerides as Potential Biomarkers of Patients at Major Risk for Pharmacological Therapy in Gestational Diabetes. Nutrients 2022;14(12):2502 View
  6. Mennickent D, Rodríguez A, Opazo M, Riedel C, Castro E, Eriz-Salinas A, Appel-Rubio J, Aguayo C, Damiano A, Guzmán-Gutiérrez E, Araya J. Machine learning applied in maternal and fetal health: a narrative review focused on pregnancy diseases and complications. Frontiers in Endocrinology 2023;14 View
  7. Lu H, Lu P, Hirst J, Mackillop L, Clifton D. A Stacked Long Short-Term Memory Approach for Predictive Blood Glucose Monitoring in Women with Gestational Diabetes Mellitus. Sensors 2023;23(18):7990 View
  8. Dimitri P, Savage M. Artificial intelligence in paediatric endocrinology: conflict or cooperation. Journal of Pediatric Endocrinology and Metabolism 2024;37(3):209 View
  9. Lu H, Ding X, Hirst J, Yang Y, Yang J, Mackillop L, Clifton D. Digital Health and Machine Learning Technologies for Blood Glucose Monitoring and Management of Gestational Diabetes. IEEE Reviews in Biomedical Engineering 2024;17:98 View