2025
230-OR: A Real-Time Recalibration Algorithm to Improve the Accuracy of CGM Sensors in Newborns
PRENDIN F, DELFAVERO S, CHERKERZIAN S, COBURN-SANDERSON A, ABDEL-RAHMAN R, MONTHE-DREZE C, GALDERISI A, SEN S, FACCHINETTI A. 230-OR: A Real-Time Recalibration Algorithm to Improve the Accuracy of CGM Sensors in Newborns. Diabetes 2025, 74 DOI: 10.2337/db25-230-or.Peer-Reviewed Original ResearchNeonatal hypoglycemiaContinuous glucose monitoringLong-term neurodevelopmental sequelaeMean absolute relative differenceNeonatal blood glucoseBlood glucoseNon-diabetic controlsIRB-approved studyNeurodevelopmental sequelaeThird trimesterStatistically significant improvementPhysiology of neonatesPregnant womenCGM sensorsReal-time recalibrationNewbornsContinuous glucose monitoring sensorContinuous glucose monitoring dataStandard careReal-timeSensor accuracyAccuracy of continuous glucose monitoringAlgorithmRecalibration algorithmDexcom G6 sensor
2024
Low-Cost CO2 NDIR Sensors: Performance Evaluation and Calibration Using Machine Learning Techniques
Dubey R, Telles A, Nikkel J, Cao C, Gewirtzman J, Raymond P, Lee X. Low-Cost CO2 NDIR Sensors: Performance Evaluation and Calibration Using Machine Learning Techniques. Sensors 2024, 24: 5675. PMID: 39275586, PMCID: PMC11397870, DOI: 10.3390/s24175675.Peer-Reviewed Original ResearchMachine learning techniquesLearning techniquesNon-linear datasetsSensor accuracyStacking ensemble modelLow-cost sensor applicationsMachine learning modelsPotential of machine learningReference-grade instrumentsTree-based modelsMachine learningLearning modelsSensor measurementsPerformance evaluationEnsemble modelSensor calibrationSensor performanceSensorRandom forest regressionMachineSensor applicationsAccuracyForest regressionIndividual modelsPerformance
2005
Limitations of statistical measures of error in assessing the accuracy of continuous glucose sensors.
Kollman C, Wilson DM, Wysocki T, Tamborlane WV, Beck RW. Limitations of statistical measures of error in assessing the accuracy of continuous glucose sensors. Diabetes Technology & Therapeutics 2005, 7: 665-72; discussion 673-4. PMID: 16241865, PMCID: PMC1805466, DOI: 10.1089/dia.2005.7.665.Peer-Reviewed Original ResearchConceptsStatistical methodsStatistical measuresModified gridComputer simulationsObserved p-valuesContinuous error grid analysisGrid analysisIdentical accuracyNull hypothesisActual dataGridSimulationsAccuracyErrorSensor accuracySubject effectsCorrelation patternsProbabilityOperating characteristicsInconsistent notions
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