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

mHealth for Symptom and Disease Monitoring, Chronic Disease Management (1317) Human Factors and Usability Case Studies (748) Food Sciences and Nutrition Engineering (51) Imaging Informatics (187) Machine Learning (1400) Instruments and Questionnaires for Nutrition and Food Intake (159) Usability of Apps and User Perceptions of mHealth (902) Apps, Mobile, Wearables for Diabetes (288) Diabetes Education and Self-Management in Childhood and Adolescence (31)

Published on in Vol 8, No 10 (2020): October

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/22074, first published .
Carbohydrate Counting App Using Image Recognition for Youth With Type 1 Diabetes: Pilot Randomized Control Trial

Carbohydrate Counting App Using Image Recognition for Youth With Type 1 Diabetes: Pilot Randomized Control Trial

Carbohydrate Counting App Using Image Recognition for Youth With Type 1 Diabetes: Pilot Randomized Control Trial

Authors of this article:

Jeffrey E Alfonsi1, 2 Author Orcid Image ;   Elizabeth E Y Choi2 Author Orcid Image ;   Taha Arshad3 Author Orcid Image ;   Stacie-Ann S Sammott3 Author Orcid Image ;   Vanita Pais3 Author Orcid Image ;   Cynthia Nguyen4 Author Orcid Image ;   Bryan R Maguire5 Author Orcid Image ;   Jennifer N Stinson4, 6 Author Orcid Image ;   Mark R Palmert3, 7 Author Orcid Image
Article Authors Cited by (40) Tweetations (5) Metrics

Journals

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  5. Murphy J, McSharry J, Hynes L, Molloy G. A Smartphone App to Support Adherence to Inhaled Corticosteroids in Young Adults With Asthma: Multi-Methods Feasibility Study. JMIR Formative Research 2021;5(9):e28784 View
  6. Chotwanvirat P, Hnoohom N, Rojroongwasinkul N, Kriengsinyos W. Feasibility Study of an Automated Carbohydrate Estimation System Using Thai Food Images in Comparison With Estimation by Dietitians. Frontiers in Nutrition 2021;8 View
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  9. Fu H, Wyman J, Peden-McAlpine C, Draucker C, Schleyer T, Adam T. App Design Features Important for Diabetes Self-management as Determined by the Self-Determination Theory on Motivation: Content Analysis of Survey Responses From Adults Requiring Insulin Therapy. JMIR Diabetes 2023;8:e38592 View
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  13. Yun J, Shin J, Lee H, Kim D, Choi I, Kim M. Characteristics and Potential Challenges of Digital-Based Interventions for Children and Young People: Scoping Review. Journal of Medical Internet Research 2023;25:e45465 View
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  15. Deniz-Garcia A, Fabelo H, Rodriguez-Almeida A, Zamora-Zamorano G, Castro-Fernandez M, Alberiche Ruano M, Solvoll T, Granja C, Schopf T, Callico G, Soguero-Ruiz C, Wägner A. Quality, Usability, and Effectiveness of mHealth Apps and the Role of Artificial Intelligence: Current Scenario and Challenges. Journal of Medical Internet Research 2023;25:e44030 View
  16. AlBabtain S, AlAfif N, AlDisi D, AlZahrani S. Manual and Application-Based Carbohydrate Counting and Glycemic Control in Type 1 Diabetes Subjects: A Narrative Review. Healthcare 2023;11(7):934 View
  17. Pi L, Shi X, Wang Z, Zhou Z. Effect of smartphone apps on glycemic control in young patients with type 1 diabetes: A meta-analysis. Frontiers in Public Health 2023;11 View
  18. Zhang M, Zhang H, Zhu R, Yang H, Chen M, Wang X, Li Z, Xiong Z. Factors affecting the willingness of patients with type 2 diabetes to use digital disease management applications: a cross-sectional study. Frontiers in Public Health 2023;11 View
  19. Clerc A. Nutrition education to type 1 diabetes patients: few changes over the time. Frontiers in Clinical Diabetes and Healthcare 2023;4 View
  20. Sze W, Kow S. Perspectives and Needs of Malaysian Patients With Diabetes for a Mobile Health App Support on Self-Management of Diabetes: Qualitative Study. JMIR Diabetes 2023;8:e40968 View
  21. Uliana G, Camara L, Paracampo C, da Costa J, Gomes D. Characteristics of carbohydrate counting practice associated with adequacy of glycated hemoglobin in adults with type 1 diabetes mellitus in Brazil. Frontiers in Endocrinology 2023;14 View
  22. Wiyono L, Ghitha N, Clarisa D, Larasati A. Carbohydrate counting implementation on pediatric type 1 diabetes mellitus: systematic review and meta-analysis. Annals of Pediatric Endocrinology & Metabolism 2023;28(3):206 View
  23. Weiss R. Closed loop insulin delivery–Opportunities and limitations. Journal of Diabetes 2023;15(12):1103 View
  24. Zrubka Z, Kertész G, Gulácsi L, Czere J, Hölgyesi Á, Nezhad H, Mosavi A, Kovács L, Butte A, Péntek M. The Reporting Quality of Machine Learning Studies on Pediatric Diabetes Mellitus: Systematic Review. Journal of Medical Internet Research 2024;26:e47430 View
  25. Elamin S, Redzuan A, Aziz S, Hamdan S, Masmuzidin M, Shah N. Impacts of Educational Interventions on Glycemic Control in Children and Adolescents with Type 1 Diabetes Mellitus. Archives of Pharmacy Practice 2023;14(4):13 View
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  28. Khalifa M, Albadawy M. Artificial intelligence for diabetes: Enhancing prevention, diagnosis, and effective management. Computer Methods and Programs in Biomedicine Update 2024;5:100141 View
  29. Hasanah I, Sari A, Nursalam N, Safinatunnaja B, Krisnana I, Basuni H, Haikal Z, Ramdani W. Impact of Mobile and Web Health Apps on Pediatric Chronic Disease Management and Quality of Life: An Update Systematic Review. Africa Journal of Nursing and Midwifery 2024 View
  30. Tarricone R, Petracca F, Svae L, Cucciniello M, Ciani O. Which behaviour change techniques work best for diabetes self-management mobile apps? Results from a systematic review and meta-analysis of randomised controlled trials. eBioMedicine 2024;103:105091 View
  31. Iqhrammullah M, Yudhistira Refin R, Fitria Andika F, Amirah S, Fahd Abdurrahman M, Alina M, Yufika A, Abdullah A. Dropout rate in clinical trials of smartphone apps for diabetes management: A meta-analysis. Diabetes Research and Clinical Practice 2024;212:111723 View
  32. Scidà G, Corrado A, Abuqwider J, Lupoli R, Rainone C, Della Pepa G, Masulli M, Annuzzi G, Bozzetto L. Postprandial Glucose Control With Different Hybrid Closed-Loop Systems According to Type of Meal in Adults With Type 1 Diabetes. Journal of Diabetes Science and Technology 2024 View
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Books/Policy Documents

  1. Matsumoto A. Wearable Biosensing in Medicine and Healthcare. View
  2. Chen C, Laffel L. Textbook of Diabetes. View