Personalized glucose forecasting for people with type 1 diabetes using large language models.

Journal: Computer methods and programs in biomedicine
PMID: 40188577

Abstract

BACKGROUND AND OBJECTIVE: Type 1 Diabetes (T1D) is an autoimmune disease that requires exogenous insulin via Multiple Daily Injections (MDIs) or subcutaneous pumps to maintain targeted glucose levels. Despite the advances in Continuous Glucose Monitoring (CGM), controlling glucose levels remains challenging. Large Language Models (LLMs) have produced impressive results in text processing, but their performance with other data modalities remains unexplored. The aim of this study is three-fold. First, to evaluate the effectiveness of LLM-based models for glucose forecasting. Second, to compare the performance of different models for predicting glucose in T1D individuals treated with MDIs and pumps. Lastly, to create a personalized approach based on patient-specific training and adaptive model selection.

Authors

  • Francisco J Lara-Abelenda
    Department of Signal Theory and Communications, Telematics and Computing Systems, Rey Juan Carlos University, Madrid, Spain. Electronic address: francisco.lara@urjc.es.
  • David Chushig-Muzo
    Department of Signal Theory and Communications, Telematics and Computing Systems, Rey Juan Carlos University, Madrid, Spain. Electronic address: david.chushig@urjc.es.
  • Pablo Peiro-Corbacho
    Department of Signal Theory and Communications, Telematics and Computing Systems, Rey Juan Carlos University, Madrid, Spain. Electronic address: pablo.peiro@urjc.es.
  • Ana M Wägner
    Instituto Universitario de Investigaciones Biomédicas y Sanitarias, Universidad de Las Palmas de Gran Canaria, Las Palmas de Gran Canaria, Spain. Electronic address: ana.wagner@ulpgc.es.
  • Conceição Granja
    Norwegian Centre for E-health Research, University Hospital of North, Norway, Tromsø, Norway. Electronic address: conceicao.granja@ehealthresearch.no.
  • Cristina Soguero-Ruiz
    Department of Signal Theory and Communications, Telematics and Computing Systems, Rey Juan Carlos University, Madrid, Spain. Electronic address: cristina.soguero@urjc.es.

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