Episode-Driven Insights: Can Large Language Models Tackle Multimodal Diabetes Data?

Abstract excerpt

This study explores the potential of state-of-the-art large language models (LLM) to scaffold type 1 diabetes management by automating the analysis of multimodal diabetes device data, including blood glucose, carbohydrate, and insulin. By conducting a series of empirically grounded data analysis tasks, such as detecting glycemic episodes, clustering similar episodes into patterns, identifying counterfactual days,...

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• GPT gene
• Language
• Mental Disorders
• Phenotype

Identifiers and source

Literature Corpus work

b1d098df-d408-5f76-a77d-da44461f1f21

DOI

10.1101/2025.04.24.25326385