Mostrando 6 resultados de: 6
Publisher
Journal of Diabetes Science and Technology(2)
2014 IEEE-EMBS International Conference on Biomedical and Health Informatics, BHI 2014(1)
BMC Medical Informatics and Decision Making(1)
IFMBE Proceedings(1)
PLoS ONE(1)
Can continuous glucose monitoring identify risk factors in type 1 and type 2 diabetes? A literature review
Conference ObjectAbstract: Self-monitoring of blood glucose has been used for many years to control glucose levels in diabeticPalabras claves:Autores:Cancela J., Cobelli C., Facchinetti A., Ficο G., Isabel M.M., María Teresa ArredondoFuentes:scopusExploring the Frequency Domain of Continuous Glucose Monitoring Signals to Improve Characterization of Glucose Variability and of Diabetic Profiles
ArticleAbstract: Background: Continuous glucose monitoring (CGM) devices measure interstitial glucose concentrationsPalabras claves:continuous glucose monitoring, glucose variability, type 1 diabetes mellitus, Type 2 Diabetes mellitusAutores:Cancela J., Cobelli C., Fabris C., Facchinetti A., Ficο G., Gabriel R., Hernanzez L., Isabel M.M., María Teresa ArredondoFuentes:scopusExpected accuracy of proximal and distal temperature estimated by wireless sensors, in relation to their number and position on the skin
ArticleAbstract: A popular method to estimate proximal/distal temperature (TPROX and TDIST) consists in calculating aPalabras claves:Autores:Amodio P., Bolognesi M., Camila Montesinos-Guevara, Facchinetti A., Garrido M., Longato E., Mani A., Montagnese S., Saccardo D., Sparacino G.Fuentes:googlescopusParsimonious Description of Glucose Variability in Type 2 Diabetes by Sparse Principal Component Analysis
ArticleAbstract: Background: Abnormal glucose variability (GV) is a risk factor for diabetes complications, and tensPalabras claves:continuous glucose monitoring, glucose variability, type 1 diabetes, Type 2 DiabetesAutores:Cobelli C., Fabris C., Facchinetti A., Ficο G., María Teresa Arredondo, Sambo F.Fuentes:scopusUser requirements for incorporating diabetes modeling techniques in disease management tools
Conference ObjectAbstract: Type 2 Diabetes Mellitus (T2DM) is the most common form of diabetes. Early identification of peoplePalabras claves:Health Technology Assessment, Type 2 Diabetes modeling, User requirementsAutores:Bellazzi R., Cancela J., Cobelli C., Dagliati A., Facchinetti A., Fernandez-Llatas C., Ficο G., Guillén A., María Teresa Arredondo, Millana A.M., Sacchi L., Sambo F., Segagni D., Traver V., Verdú J.Fuentes:scopusWhat do healthcare professionals need to turn risk models for type 2 diabetes into usable computerized clinical decision support systems? Lessons learned from the MOSAIC project
ArticleAbstract: Background: To understand user needs, system requirements and organizational conditions towards succPalabras claves:Computerized decision support systems, Human centred design, Multi-disciplinary approach, Risk modelling, Type 2 DiabetesAutores:Bellazzi R., Cancela J., Chiovato L., Cobelli C., Dagliati A., Facchinetti A., Ficο G., Gabriel-Sanchez R., Groop L., Hernanzez L., Manero L., María Teresa Arredondo, Martinez-Millana A., Merino-Torres J.F., Nikita K.S., Ottaviano M., Posada J., Sacchi L., Traver V., Verdú J., Zarkogianni K.Fuentes:scopus