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Exploring the Potential of an AI-Integrated Cloud-Based mHealth Platform for Enhanced Type 2 Diabetes Mellitus Management

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Proceedings of the 15th International Conference on Ubiquitous Computing & Ambient Intelligence (UCAmI 2023) (UCAmI 2023)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 835))

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Abstract

Type 2 Diabetes Mellitus (T2DM) is a globally escalating health issue, with its complications significantly reducing life expectancy and imposing considerable economic and social burdens. Particularly in Chile, prevalence soars to 25–30% among individuals aged 65 and over from mid to low socioeconomic backgrounds. However, only 34% of T2DM patients achieve a target glycated hemoglobin (HbA1c) level of less than 7%. Our proposed project aims to address this challenge by developing and validating an Artificial Intelligence (AI)-integrated, cloud-based mobile health (mHealth) platform designed to enhance T2DM management. This platform facilitates lifestyle modifications and medication adherence, reducing treatment burden, while fostering patient education and self-management. It leverages biometric sensors in smartphones and wearable devices to generate metabolic control indicators to improve glycemic control beyond HbA1c and utilizes AI image processing techniques for early detection of feet ulcers. The mHealth concept, bolstered by increasing mobile connectivity, integrates patients and health providers into digital platforms, thereby creating a collaborative care model. Evidence has shown that multidimensional strategies have superior outcomes to unidimensional approaches, emphasizing the importance of incorporating various determinants into T2DM management. This novel AI-integrated cloud-based mHealth platform has the potential to revolutionize T2DM care by providing comprehensive, personalized, and efficient management solutions that not only address medical needs but also empower patients. By integrating cutting-edge AI and mHealth technology, our project is set to transform the landscape of T2DM management and improve the quality of life for millions of patients.

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Acknowledgements

This work was partially supported by a grant from Red de Salud UCChristus and Glik.

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Authors and Affiliations

  1. Escuela de Medicina, Pontificia Universidad Católica de Chile, Santiago, Chile

    Michel Bergoeing & Paulina Jofré

  2. Computer Science Department, Pontificia Universidad Católica de Chile, Santiago, Chile

    Andres Neyem, Juan Chacón, Richard Morales & Matías Giddings

  3. National Center for Artificial Intelligence (CENIA), Santiago, Chile

    Andres Neyem

  4. Hospital Clínico Eloísa Díaz La Florida, Santiago, Chile

    Paulina Jofré & Camila Hernández

Authors
  1. Michel Bergoeing
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  2. Andres Neyem
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  4. Camila Hernández
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  5. Juan Chacón
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  6. Richard Morales
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  7. Matías Giddings
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Corresponding author

Correspondence to Michel Bergoeing .

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Editors and Affiliations

  1. MAmI Research Lab, Castilla-La Mancha University, Ciudad Real, Spain

    José Bravo

  2. Anahuac University, Mérida, Yucatán, Mexico

    Gabriel Urzáiz

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© 2023 The Author(s), under exclusive license to Springer Nature Switzerland AG

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Bergoeing, M. et al. (2023). Exploring the Potential of an AI-Integrated Cloud-Based mHealth Platform for Enhanced Type 2 Diabetes Mellitus Management. In: Bravo, J., Urzáiz, G. (eds) Proceedings of the 15th International Conference on Ubiquitous Computing & Ambient Intelligence (UCAmI 2023). UCAmI 2023. Lecture Notes in Networks and Systems, vol 835. Springer, Cham. https://doi.org/10.1007/978-3-031-48306-6_10

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