Mobile Artificial Intelligence Solution for Diabetes Adaptive Care

Project Information

MELISSA

Grant agreement ID: 101057730

DOI

10.3030/101057730

EC signature date 23 May 2022

Start date 1 June 2022

End date 31 May 2027

Funded under

• Health

Total cost

€ 6 061 709,00

EU contribution

€ 5 986 709,00

Coordinated by

UNIVERSITEIT MAASTRICHT
Netherlands

CORDIS provides links to public deliverables and publications of HORIZON projects.

Links to deliverables and publications from FP7 projects, as well as links to some specific result types such as dataset and software, are dynamically retrieved from OpenAIRE .

Deliverables

Documents, reports (7)

Questionnaires for user requirements

Questionnaires for user: The questionnaires will consist of questions related to diabetes management and treatment as well as the user’s familiarity with diabetes-related apps.

Standard Operational Procedures

Standard Operational Procedures of the clinical studies of WP4

Audio-visual material

Audio-visual material will include an animated video to explain key features and results of the project.

End-user survey

End-user survey: Products/apps which already exist in the market related to diabetes will be reviewed and analyzed regarding their pros and cons and the benefit of the new app approach of the MELISSA project will be compared

First study subject approvals package
Ethical framework for a trustworthy implementation of ABBA

Recommendations for the trustworthy implementation of AI-driven diabetes management apps, addressing ethical obstacles and proposing insights to mitigate them.

Final recruitment plan

Final plan on recruiting of patients to the clinical studies of WP4

Websites, patent fillings, videos etc. (2)

Public project website

The website will inform the public about the projects aims updates and results The website will be continuously updated throughout the projects lifetime Links to social media will be implemented as well

Results for ABBA's in-silico validation

Results of the in-silico simulations achieved by the algorithm to be integrated into MELISSA's mobile application

Publications

Peer reviewed articles (8)

The effect of bolus advisors on glycaemic parameters in adults with diabetes on intensive insulin therapy: A systematic review with meta‐analysis

Author(s): Elisabeth J. den Brok; Cecilie H. Svensson; Maria Panagiotou; Marleen M. J. van Greevenbroek; Peter R. Mertens; Andriani Vazeou; Asimina Mitrakou; Konstantinos Makrilakis; Gregor H. L. M. Franssen; Sa
Published in: Diabetes, Obesity and Metabolism, 2024, ISSN 1463-1326
Publisher: Wiley
DOI: 10.48350/194556

Nutrients

Author(s): Ioannis Papathanail; Lubnaa Abdur Rahman; Lorenzo Brigato; Natalie Bez; Maria Vasiloglou; Klazine van der Horst; Stavroula Mougiakakou
Published in: Nutrients, 2023, ISSN 2072-6643
Publisher: MDPI
DOI: 10.48350/186190

Position: There are no champions in long-term time series forecasting

Author(s): Brigato, L., Morand, R., Strømmen, K., Panagiotou, M., Schmidt, M., & Mougiakakou, S
Published in: Transactions on Machine Learning Research, 2026, ISSN 2835-8856
Publisher: Journal of Machine Learning Research Inc
DOI: 10.48550/ARXIV.2502.14045

Diabetic Medicine

Author(s): Elisabeth J. den Brok, Cecilie Hornborg‐Svensson, Nefeli M. Dimitropoulou, Sofie Broeng‐Mikkelgaard, Mikkel T. Olsen, Lubnaa Abdur Rahman, Ioannis Papathanail, Antje Wiede, Juliane Peters, Peter R. Mertens, Eva Zikou, Georgios Karamanakos, Stavros Athanasopoulos, Asimina Mitrakou, Konstantinos Makrilakis, Sander M. J. van Kuijk, Stavroula Mougiakakou, Marleen M. J. van Greevenbroek, Ulrik Pedersen‐Bjergaard, Bastiaan E. de Galan, Cassy F. Dingena, null null
Published in: Diabetic Medicine, Issue 42, 2025, ISSN 0742-3071
Publisher: Blackwell Publishing Inc.
DOI: 10.1111/DME.70140

Nutrients

Author(s): Lubnaa Abdur Rahman, Vasileios Dedousis, Ioannis Papathanail, Rooholla Poursoleymani, Maria Kafyra, Ioanna Panagiota Kalafati, Stavroula Georgia Mougiakakou
Published in: Nutrients, Issue 18, 2026, ISSN 2072-6643
Publisher: Multidisciplinary Digital Publishing Institute (MDPI)
DOI: 10.3390/NU18060938

IEEE Access

Author(s): Panagiotou, M., Brigato, L., Streit, V., Hayoz, A., Proennecke, S., Athanasopoulos, S., ... & Mougiakakou, S.
Published in: IEEE Access, 2025, ISSN 2169-3536
Publisher: IEEE Xplore
DOI: 10.1109/ACCESS.2025.3600738

Role of artificial intelligence in enhancing insulin recommendations and therapy outcomes

Author(s): Panagiotou, Maria; Strommen, Knut; Brigato, Lorenzo; de Galan, Bastiaan E.; Mougiakakou, Stavroula
Published in: Die Diabetologie, 2025, ISSN 2731-7447
Publisher: Springer Nature
DOI: 10.48550/ARXIV.2503.18592

Diabetes, Obesity and Metabolism

Author(s): Elisabeth J. den Brok, Cecilie H. Svensson, Mikkel T. Olsen, Nefeli M. Dimitropoulou, Sander M. J. van Kuijk, Maria Panagiotou, Lubnaa Abdur Rahman, Stephan Proennecke, Peter R. Mertens, Stavros Athanasopoulos, Cassy F. Dingena, Konstantinos Makrilakis, Stavroula Mougiakakou, Ulrik Pedersen‐Bjergaard, Bastiaan E. de Galan, null null
Published in: Diabetes, Obesity and Metabolism, Issue 28, 2026, ISSN 1462-8902
Publisher: Wiley
DOI: 10.1111/DOM.70879

Conference proceedings (4)

A Comparative Analysis of Sensor-, Geometry-, and Neural-Based Methods for Food Volume Estimation

Author(s): Lubnaa Abdur Rahman, Ioannis Papathanail, Lorenzo Brigato, Stavroula Mougiakakou
Published in: Proceedings of the 8th International Workshop on Multimedia Assisted Dietary Management, 2023, ISBN 979-8-4007-0284-6
Publisher: ACM
DOI: 10.1145/3607828.3617794

A Complete AI-Based System for Dietary Assessment and Personalized Insulin Adjustment in Type 1 Diabetes Self-management

Author(s): Panagiotou, Maria, Ioannis Papathanail, Lubnaa Abdur Rahman, Lorenzo Brigato, Natalie S. Bez, Maria F. Vasiloglou, Thomai Stathopoulou, Bastiaan E. de Galan, Ulrik Pedersen-Bjergaard, Klazine van der Horst, Stavroula Mougiakakou
Published in: International Conference on Computer Analysis of Images and Patterns, 2023, ISBN 978-3-031-44240-7
Publisher: Springer, Cham
DOI: 10.1007/978-3-031-44240-7_8

Introducing the Swiss Food Knowledge Graph: AI for Context-Aware Nutrition Recommendation

Author(s): Abdur Rahman, L., Papathanail, I., Mougiakakou, S
Published in: Proceedings of the 1st International Workshop on Multi-modal Food Computing, 2025, ISBN 979-8-4007-2046-8
Publisher: ACM
DOI: 10.1145/3746264.3760494

A SAM Based Tool for Semi-Automatic Food Annotation

Author(s): Rahman, Lubnaa Abdur; Papathanail, Ioannis; Brigato, Lorenzo; Mougiakakou, Stavroula
Published in: Frontiers in Artificial Intelligence and Applications ISBN: 9781643685489, 2024
Publisher: IOS Press
DOI: 10.48550/ARXIV.2410.19756

Book chapters (2)

Benchmarking Post-Hoc Unknown-Category Detection in Food Recognition

Author(s): Lubnaa Abdur Rahman, Ioannis Papathanail, Lorenzo Brigato, Stavroula Mougiakakou
Published in: Lecture Notes in Computer Science, Pattern Recognition. ICPR 2024 International Workshops and Challenges, 2025
Publisher: Springer Nature Switzerland
DOI: 10.48550/ARXIV.2503.18548

Food Recognition and Nutritional Apps

Author(s): Rahman, Lubnaa Abdur; Papathanail, Ioannis; Brigato, Lorenzo; Spanakis, Elias K.; Mougiakakou, Stavroula
Published in: Diabetes Digital Health, Telehealth, and Artificial Intelligence, 2023, ISBN 9780323906760
Publisher: Elsevier