The importance of interpreting machine learning models for blood glucose prediction in diabetes: an analysis using SHAP

Machine learning has become a popular tool for learning models of complex dynamics from biomedical data. In Type 1 Diabetes (T1D) management, these models are increasingly been integrated in decision support systems (DSS) to forecast glucose levels and provide preventive therapeutic suggestions, lik...

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Detalles Bibliográficos
Autores principales: Prendin, Francesco, Pavan, Jacopo, Cappon, Giacomo, Del Favero, Simone, Sparacino, Giovanni, Facchinetti, Andrea
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10558434/
https://www.ncbi.nlm.nih.gov/pubmed/37803177
http://dx.doi.org/10.1038/s41598-023-44155-x

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10558434/
https://www.ncbi.nlm.nih.gov/pubmed/37803177
http://dx.doi.org/10.1038/s41598-023-44155-x

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