Published on in Vol 8, No 3 (2020): March
Preprints (earlier versions) of this paper are
available at
https://preprints.jmir.org/preprint/15294, first published
.

Journals
- Steenkamp D, Eby E, Gulati N, Liao B. Adherence and Persistence to Insulin Therapy in People with Diabetes: Impact of Connected Insulin Pen Delivery Ecosystem. Journal of Diabetes Science and Technology 2022;16(4):995 View
- Pfisterer K, Amelard R, Chung A, Syrnyk B, MacLean A, Keller H, Wong A. Automated food intake tracking requires depth-refined semantic segmentation to rectify visual-volume discordance in long-term care homes. Scientific Reports 2022;12(1) View
- Schönenberger K, Cossu L, Prendin F, Cappon G, Wu J, Fuchs K, Mayer S, Herzig D, Facchinetti A, Bally L. Digital Solutions to Diagnose and Manage Postbariatric Hypoglycemia. Frontiers in Nutrition 2022;9 View
- Jia W, Ren Y, Li B, Beatrice B, Que J, Cao S, Wu Z, Mao Z, Lo B, Anderson A, Frost G, McCrory M, Sazonov E, Steiner-Asiedu M, Baranowski T, Burke L, Sun M. A Novel Approach to Dining Bowl Reconstruction for Image-Based Food Volume Estimation. Sensors 2022;22(4):1493 View
- Barmanray R, Kyi M, Fourlanos S. Assistive technology for diabetes management: a toolkit. British Journal of Healthcare Management 2022;28(5):118 View
- Amugongo L, Kriebitz A, Boch A, Lütge C. Mobile Computer Vision-Based Applications for Food Recognition and Volume and Calorific Estimation: A Systematic Review. Healthcare 2022;11(1):59 View
- Vasiloglou M, Marcano I, Lizama S, Papathanail I, Spanakis E, Mougiakakou S. Multimedia Data-Based Mobile Applications for Dietary Assessment. Journal of Diabetes Science and Technology 2023;17(4):1056 View
- Moshfegh A, Rhodes D, Martin C. National Food Intake Assessment: Technologies to Advance Traditional Methods. Annual Review of Nutrition 2022;42(1):401 View
- Karabay A, Bolatov A, Varol H, Chan M. A Central Asian Food Dataset for Personalized Dietary Interventions. Nutrients 2023;15(7):1728 View
- Zhang S, Callaghan V, Che Y. Image-based methods for dietary assessment: a survey. Journal of Food Measurement and Characterization 2024;18(1):727 View
- Serra M, Alceste D, Hauser F, Hulshof P, Meijer H, Thalheimer A, Steinert R, Gerber P, Spector A, Gero D, Bueter M. Assessing daily energy intake in adult women: validity of a food-recognition mobile application compared to doubly labelled water. Frontiers in Nutrition 2023;10 View
- Shonkoff E, Cara K, Pei X, Chung M, Kamath S, Panetta K, Hennessy E. AI-based digital image dietary assessment methods compared to humans and ground truth: a systematic review. Annals of Medicine 2023;55(2) View
- Zhang R, Ouyang D, He L, Kuang L, Bai H. Recognize after early fusion: the Chinese food recognition based on the alignment of image and ingredients. Multimedia Systems 2024;30(2) View
- Baumgartner M, Kuhn C, Nakas C, Herzig D, Bally L. Carbohydrate Estimation Accuracy of Two Commercially Available Smartphone Applications vs Estimation by Individuals With Type 1 Diabetes: A Comparative Study. Journal of Diabetes Science and Technology 2025;19(6):1570 View
- Chotwanvirat P, Prachansuwan A, Sridonpai P, Kriengsinyos W. Advancements in Using AI for Dietary Assessment Based on Food Images: Scoping Review. Journal of Medical Internet Research 2024;26:e51432 View
- Ma P, Jia X, Gao M, Yi Z, Tsai S, He Y, Zhen D, Blaustein R, Wang Q, Wei C, Fan B, Wang F. Innovative food supply chain through spatial computing technologies: A review. Comprehensive Reviews in Food Science and Food Safety 2024;23(6) View
- Zhang R, Ouyang D, Li X, Bai H, Zhang C, He L. Learning multi-scale features automatically from food and ingredients. Multimedia Systems 2025;31(3) View
- Pujia C, Ferro Y, Mazza E, Maurotti S, Montalcini T, Pujia A. The Role of Mobile Apps in Obesity Management: Systematic Review and Meta-Analysis. Journal of Medical Internet Research 2025;27:e66887 View
- Barmanray R, Kyi M, Fourlanos S. Assistive technology for diabetes management: a toolkit. Practice Nursing 2025;36(10):390 View
- Piazza C, Laesser C, Kastrati L, Barnard-Kelly K, Nakas C, Herzig D, Bally L. App-based automated meal analysis in adults with type 1 diabetes using automated insulin delivery: a randomized controlled trial. eClinicalMedicine 2025;89:103537 View
- Fragozo-Ramos M, Schenker G, Hepprich M, Gallo-Villegas J, Züger T, Garcia-Tirado J, Hariyanto T. GIP/GLP-1RA as adjunctive to automated insulin delivery in adults with Type 1 diabetes (the AID-JUNCT trial): Study protocol for a prospective, randomized, clinical trial. PLOS One 2025;20(10):e0335060 View
- Choochaiwattana W, Jaruariyanon P, Jitpranee A, Deecharoen R, Kaewpradup T, Chusak C, Adisakwattana S. AI powered dietary proportion assessment for improving accuracy and practicality of the balanced meal plate model. Scientific Reports 2025 View
Books/Policy Documents
- Nagarajan B, Khatun R, Bolaños M, Aguilar E, Angelini L, El Kamali M, Mugellini E, Khaled O, Boqué N, Tarro L, Radeva P. Digital Health Technology for Better Aging. View
- Chummun P, Suddul G, Armoogum S. Proceedings of World Conference on Information Systems for Business Management. View
- Abdur Rahman L, Papathanail I, Brigato L, Spanakis E, Mougiakakou S. Diabetes Digital Health, Telehealth, and Artificial Intelligence. View
- Arias Velásquez R, Dreyfus B, Rosendo E. Artificial Intelligence for System Oriented Design. View
Conference Proceedings
- Dubey S, Kraft D, Drueeke N, Bieber G. Proceedings of the 8th international Workshop on Sensor-Based Activity Recognition and Artificial Intelligence. Survey on food intake methods using visual technologies View
- Setyawan R, Perdana R, Harilegawa M, Balantimuhe A, Basuki A. Proceedings of the 8th International Conference on Sustainable Information Engineering and Technology. AVIG: A Real-Time Visual Inspection for Guava Grading System Using Computer Vision and XGBoost View
