A Complete AI-Based System for Dietary Assessment and Personalized Insulin Adjustment in Type 1 Diabetes Self-management
Publikation: Bidrag til bog/antologi/rapport › Konferencebidrag i proceedings › Forskning › fagfællebedømt
People living with type 1 diabetes (PwT1D) face multiple challenges in self-managing their blood glucose levels, including the need for accurate carbohydrate counting, and the requirements of adjusting insulin dosage. Our paper aims to alleviate the demands of diabetes self-management by developing a complete system that employs computer vision to estimate the carbohydrate content of meals and utilizes reinforcement learning to personalize insulin dosing. Our findings demonstrate that this system results in a significantly greater percentage of time spent in the target glucose range compared to the combined standard bolus calculator treatment and carbohydrate counting. This approach could potentially improve glycaemic control for PwT1D and reduce the burden of carbohydrate and insulin dosage estimations.
| Originalsprog | Engelsk |
|---|---|
| Titel | Computer Analysis of Images and Patterns - 20th International Conference, CAIP 2023, Proceedings |
| Redaktører | Nicolas Tsapatsoulis, Andreas Lanitis, Marios Pattichis, Constantinos Pattichis, Christos Kyrkou, Efthyvoulos Kyriacou, Zenonas Theodosiou, Andreas Panayides |
| Forlag | Springer |
| Publikationsdato | 2023 |
| Sider | 77-86 |
| ISBN (Trykt) | 978-3-031-44239-1 |
| ISBN (Elektronisk) | 978-3-031-44240-7 |
| DOI | |
| Status | Udgivet - 2023 |
| Begivenhed | 20th International Conference on Computer Analysis of Images and Patterns, CAIP 2023 - Limassol, Cypern Varighed: 25 sep. 2023 → 28 sep. 2023 |
Konference
| Konference | 20th International Conference on Computer Analysis of Images and Patterns, CAIP 2023 |
|---|---|
| Land | Cypern |
| By | Limassol |
| Periode | 25/09/2023 → 28/09/2023 |
| Navn | Lecture Notes in Computer Science |
|---|---|
| Vol/bind | 14185 |
| ISSN | 0302-9743 |
Bibliografisk note
Funding Information:
Acknowledgements. This project was partially supported by EU’s H2020 Research and Innovation Programme (Grant Agreement No 739578) and the Government of the Republic of Cyprus.
Funding Information:
Acknowledgement. This work was supported by the SEARCH project, UT Theme Call 2020, Faculty of Electrical Engineering, Mathematics and Computer Science, University of Twente.
Funding Information:
Acknowledgements. This work was supported in part by the European Commission and the Swiss Confederation - State Secretariat for Education, Research and Innovation (SERI) within the project 101057730 Mobile Artificial Intelligence Solution for Diabetes Adaptive Care (MELISSA). The food images used to evaluate the system have been collected within the “Nutritional assessment: comparison between an automated tool (goFOODTM) and conventional methods” study (BASEC Number: 2020-00419).
Funding Information:
This work was supported in part by the European Commission and the Swiss Confederation-State Secretariat for Education, Research and Innovation (SERI) within the project 101057730 Mobile Artificial Intelligence Solution for Diabetes Adaptive Care (MELISSA). The food images used to evaluate the system have been collected within the “Nutritional assessment: comparison between an automated tool (goFOODTM) and conventional methods” study (BASEC Number: 2020-00419).
Funding Information:
Supported by projects TED2021-129151B-I00/AEI/10.13039/ 501100011033/European Union NextGenerationEU/PRTR and PID2019-103871GB-I00 of the Spanish Ministry of Economy, Industry and Competitiveness.
Funding Information:
Acknoledgements. This work was supported by “Smart unmannEd AeRial vehiCles for Human likE monitoRing (SEARCHER)” project of the Italian Ministry of Defence (CIG: Z84333EA0D), “A Brain Computer Interface (BCI) based System for Transferring Human Emotions inside Unmanned Aerial Vehicles (UAVs)” Sapienza Research Projects (Protocol number: RM1221816C1CF63B), and the MICS (Made in Italy - Circular and Sustainable) Extended Partnership and received funding from Next-Generation EU (Italian PNRR - M4 C2, Invest 1.3 - D.D. 1551.11-10-2022, PE00000004). CUP MICS B53C22004130001. The research leading to these results has received funding from Project “Ecosistema dell’innovazione - Rome Technopole” financed by EU in Next Generation EU plan through MUR Decree n. 1051 23.06.2022 -CUP H33C22000420001.
Funding Information:
Acknowledgements. This work is supported by the European Union Civil Protection Call for proposals UCPM-2022-KN grant agreement No 101101704 (COLLARIS Network). The work is partially supported by the European Union’s Horizon 2020 research and innovation program under grant agreement No 739551 (KIOS CoE - TEAMING) and from the Republic of Cyprus through the Deputy Ministry of Research, Innovation and Digital Policy.
Funding Information:
Acknowledgment. This work is part of the project PID2019-106800RB-I00 (2019) of the Ministry of Science and Innovation (MCIN), State Research Agency MCIN/AEI/https://doi.org/10. 13039/501100011033/. It is also part of the AGROALNEXT/2022/043 project, financed by the Generalitat Valenciana, the Next Generation European Union and the Recovery, Transformation and Resilience Plan of the Government of Spain.
Funding Information:
Acknowledgment. This work is supported by ZonMw under project B3CARE (project number 104006003). This project has received funding from the EU Horizon 2020 research and innovation program under the Marie Sklodowska-Curie grant agreement No 777826. CB acknowledges support from the Dutch 4TU HTSF program Precision Medicine.
Funding Information:
This work was supported in part by the Natural Science Foundation of China under Grant Nos. 62271276, 62071266 and 61931022, in part by the Natural Science Foundation of Ningbo under Grant No. 202003N4088, and in part by Science and Technology Innovation 2025 Major Project of Ningbo under Grant No. 2022Z076.
Funding Information:
This work has been co-funded by the Normandy Region and the French National Research Agency (ANR) through a HAISCoDe Ph.D. grant. It was granted access to the HPC resources of IDRIS under the allocation 2022-AD010613618 made by GENCI, and to the computing resources of CRIANN (Normandy, France).
Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Switzerland AG 2023.
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