首页|University of Reading Reports Findings in Diabetes Mellitus Management (Machine Learning-Based Time in Patterns for Blood Glucose Fluctuation Pattern Recognitio n in Type 1 Diabetes Management: Development and Validation Study)
University of Reading Reports Findings in Diabetes Mellitus Management (Machine Learning-Based Time in Patterns for Blood Glucose Fluctuation Pattern Recognitio n in Type 1 Diabetes Management: Development and Validation Study)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – New research on Nutritional and Metabo lic Diseases and Conditions - Diabetes Mellitus Management is the subject of a r eport. According to news reporting originating in Reading, United Kingdom, by Ne wsRx journalists, research stated, “Continuous glucose monitoring (CGM) for diab etes combines noninvasive glucose biosensors, continuous monitoring, cloud compu ting, and analytics to connect and simulate a hospital setting in a person’s hom e. CGM systems inspired analytics methods to measure glycemic variability (GV), but existing GV analytics methods disregard glucose trends and patterns; hence, they fail to capture entire temporal patterns and do not provide granular insigh ts about glucose fluctuations.”
ReadingUnited KingdomEuropeCyborgsDiabetes Mellitus ManagementEmerging TechnologiesHealth and MedicineInsu lin Dependent Diabetes MellitusMachine LearningNutritional and Metabolic Dis eases and ConditionsType 1 Diabetes
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