ArticleScientific data2023
T1DiabetesGranada: a longitudinal multi-modal dataset of type 1 diabetes mellitus.
Article in Scientific data, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- Do Metrics of Temporal Glycemic Variability Reveal Abnormal Glucose Rates of Change in Type 1 Diabetes?Journal of diabetes science and technology · 2026Article
- A bimodal dataset for diabetes research.Scientific data · 2026Article
- Narrowing the A1c gap: Personalized modeling of HbA1c- continuous glucose monitor discordance in type 1 diabetes.PLOS digital health · 2026Article
- Coefficient of Variation to Assess the Reproducibility of Meal-Induced Glycemic Responses: Development of a Clustering Algorithm.JMIR diabetes · 2025Article
- CGMacros: a pilot scientific dataset for personalized nutrition and diet monitoring.Scientific data · 2025Article
- Event-triggered smart dual hormone artificial pancreas for patient-specific drug delivery.Scientific reports · 2025Article
- T1DiabetesGranada: a longitudinal multi-modal dataset of type 1 diabetes mellitus.Scientific data · 2023Article
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Authors and funding
7 authors.
Funding
Abstract
Type 1 diabetes mellitus (T1D) patients face daily difficulties in keeping their blood glucose levels within appropriate ranges. Several techniques and devices, such as flash glucose meters, have been developed to help T1D patients improve their quality of life. Most recently, the data collected via these devices is being used to train advanced artificial intelligence models to characterize the evolution of the disease and support its management. Data scarcity is the main challenge for generating these models, as most works use private or artificially generated datasets. For this reason, this work presents T1DiabetesGranada, an open under specific permission longitudinal dataset that not only provides continuous glucose levels, but also patient demographic and clinical information. The dataset includes 257 780 days of measurements spanning four years from 736 T1D patients from the province of Granada, Spain. This dataset advances beyond the state of the art as one the longest and largest open datasets of continuous glucose measurements, thus boosting the development of new artificial intelligence models for glucose level characterization and prediction.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.