Glucostats: an efficient Python library for glucose time series feature extraction and visual analysis

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Detalles Bibliográficos
Publicado en:	BMC Bioinformatics vol. 26 (2025), p. 1-17
Autor principal:	Peiro-Corbacho, Pablo
Otros Autores:	Lara-Abelenda, Francisco J, Chushig-Muzo, David, Wägner, Ana M, Granja, Conceição, Soguero-Ruiz, Cristina
Publicado:	Springer Nature B.V.
Materias:	Parallel processing Software Diabetes Hyperglycemia Trend analysis Trends Pattern recognition Hypoglycemia Python Data science Computer applications Modularity Glucose monitoring Machine learning Time series Visualization Glucose Data analysis Datasets Pattern analysis Pipelining (computers) Design Modular design Information processing Anomalies Libraries Environmental
Acceso en línea:	Citation/Abstract Full Text Full Text - PDF
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