dc.contributor
Ministerio de Economía y Competitividad (Espanya)
dc.contributor.author
Contreras, Ivan
dc.contributor.author
Vehí, Josep
dc.date.accessioned
2024-06-18T14:38:55Z
dc.date.available
2024-06-18T14:38:55Z
dc.identifier
http://hdl.handle.net/10256/15852
dc.identifier.uri
http://hdl.handle.net/10256/15852
dc.description.abstract
This work is devoted to providing patients and physicians with a novel tool to analyse and extract information for better management of type I diabetes. We use a clustering methodology based on the normalised compression distance to identify different profiles of days. The methodology has been validated using data generated by a simulator of virtual patients, which include an exercise model. Profiling daily data can help physicians and patients cope with information overload and assist in future planning for improved treatments and self-management of diabetes type 1
dc.description.abstract
Partially supported by the Spanish Ministry of Science and Innovation through grant DPI 2013-46982-C2-2-R and the Government of Catalonia trough grant
SGR14-1052
dc.format
application/pdf
dc.relation
info:eu-repo/semantics/altIdentifier/doi/10.1016/j.ifacol.2015.10.170
dc.relation
info:eu-repo/semantics/altIdentifier/eissn/1474-6670
dc.relation
DPI2013‐46982‐C2‐2‐R
dc.relation
info:eu-repo/grantAgreement/MINECO//DPI2013-46982-C2-2-R/ES/NUEVOS METODOS PARA LA EFICIENCIA Y SEGURIDAD DEL PANCREAS ARTIFICIAL DOMICILIARIO EN DIABETES TIPO 1/
dc.rights
Attribution-NonCommercial-NoDerivatives 4.0 International
dc.rights
http://creativecommons.org/licenses/by-nc-nd/4.0/
dc.rights
info:eu-repo/semantics/openAccess
dc.source
IFAC-PapersOnLine, 2015, vol. 48, núm. 20, p. 383-388
dc.source
Articles publicats (D-EEEiA)
dc.subject
Anàlisi de conglomerats
dc.subject
Cluster analysis
dc.subject
Informació, Teoria de la
dc.subject
Information theory
dc.subject
Sèries temporals -- Anàlisi
dc.subject
Time-series analysis
dc.title
Using Normalised Compression Distance to Identify Different Profiling Days in Type 1 Diabetic Patients
dc.type
info:eu-repo/semantics/article
dc.type
info:eu-repo/semantics/acceptedVersion
