The Original Clarke Error Grid Analysis (EGA)
2005; Mary Ann Liebert, Inc.; Volume: 7; Issue: 5 Linguagem: Inglês
10.1089/dia.2005.7.776
ISSN1557-8593
Autores Tópico(s)Diabetes Management and Research
ResumoDiabetes Technology & TherapeuticsVol. 7, No. 5 First Clinical Diabetes Technology Meeting; April 15–16, 2005; Pan Pacific Hotel San Francisco, CaliforniaThe Original Clarke Error Grid Analysis (EGA)William L. ClarkeWilliam L. ClarkePublished Online:21 Oct 2005https://doi.org/10.1089/dia.2005.7.776AboutSectionsPDF/EPUB Permissions & CitationsPermissionsDownload CitationsTrack CitationsAdd to favorites Back To Publication ShareShare onFacebookTwitterLinked InRedditEmail FiguresReferencesRelatedDetailsCited byPrecisión numérica y clínica en hipoglucemia de la monitorización intermitente de glucosa FreeStyle Libre a través de un transmisor NFC-Bluetooth asociado al algoritmo xDrip+ en pacientes diabéticos en insulinoterapiaEndocrinología, Diabetes y Nutrición, Vol. 70, No. 3Prediction of Blood Risk Score in Diabetes Using Deep Neural Networks20 February 2023 | Journal of Clinical Medicine, Vol. 12, No. 4Multivariate Long-Term Forecasting of T1DM: A Hybrid Econometric Model-Based Approach13 December 2022Evaluation of a Web-Based Simulation Tool for Self-Management Support in Type 1 Diabetes: A Pilot StudyIEEE Journal of Biomedical and Health Informatics, Vol. 27, No. 1Assessing Vulnerability from Its Description16 February 2023Quantification of glycated hemoglobin and glucose in vivo using Raman spectroscopy and artificial neural networks5 September 2022 | Lasers in Medical Science, Vol. 37, No. 9A machine learning-based on-demand sweat glucose reporting platform14 February 2022 | Scientific Reports, Vol. 12, No. 1Wearable flexible body matched electromagnetic sensors for personalized non-invasive glucose monitoring1 September 2022 | Scientific Reports, Vol. 12, No. 1Subcutaneously implantable electromagnetic biosensor system for continuous glucose monitoring17 October 2022 | Scientific Reports, Vol. 12, No. 1Predicting Blood Glucose Concentration after Short-Acting Insulin Injection Using Discontinuous Injection Records3 November 2022 | Sensors, Vol. 22, No. 21A 186μW Photoplethysmography-Based Noninvasive Glucose Sensing SoCIEEE Sensors Journal, Vol. 22, No. 14Noninvasive Blood Glucose Monitoring Systems Using Near-Infrared Technology—A Review27 June 2022 | Sensors, Vol. 22, No. 13Diabetes Detection and Management through Photoplethysmographic and Electrocardiographic Signals Analysis: A Systematic Review29 June 2022 | Sensors, Vol. 22, No. 13Predicting glucose level with an adapted branch predictorComputers in Biology and Medicine, Vol. 145Use of a Continuous Glucose Monitoring System in High-Risk Hospitalized Noncritically Ill Patients With Diabetes After Cardiac Surgery and During Their Transition of Care From the Intensive Care Unit During COVID-19: A Pilot StudyEndocrine Practice, Vol. 28, No. 6Development of non-invasive blood glucose regression based on near-infrared spectroscopy combined with a deep-learning method23 February 2022 | Journal of Physics D: Applied Physics, Vol. 55, No. 21An autonomous channel deep learning framework for blood glucose predictionApplied Soft Computing, Vol. 120Prediction of Glucose Concentration in Children with Type 1 Diabetes Using Neural Networks: An Edge Computing Application21 April 2022 | Bioengineering, Vol. 9, No. 5Where can you wear your Libre? 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Clarke.The Original Clarke Error Grid Analysis (EGA).Diabetes Technology & Therapeutics.Oct 2005.776-779.http://doi.org/10.1089/dia.2005.7.776Published in Volume: 7 Issue 5: October 21, 2005PDF download
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