TY  - GEN 
AU  - Baños Legrán, Oresti
AU  - Avilés-Pérez, María Dolores
AU  - Gayaroa, Álvaro
AU  - Lopez-Ibarra Lozano, Pablo J.
AU  - Muñoz Torres, Manuel Eduardo
AU  - Quesada Charneco, Miguel
AU  - Rodríguez León, Ciro
AU  - Villalonga Palliser, Claudia
PY  - 2025
SN  - 979-8-3315-8618-8
SN  - 2694-0604
UR  - https://hdl.handle.net/10481/112035
AB  - This work investigates the impact of patients’ heterogeneity, including factors such as gender, age, and clinical conditions, on the performance of machine learning models in predicting blood glucose levels in individuals with Type 1 Diabetes. Using...
LA  - eng
PB  - IEEE
TI  - Exploring the Influence of Patients’ Heterogeneity on Automated Prediction of Blood Glucose Levels in Type 1 Diabetes
DO  - 10.1109/EMBC58623.2025.11253928
ER  -