Synthetic Health data Generation for Enhancement of Non-Invasive Diabetes AI-Based Prediction
William Alberto Cruz Castañeda,
Pedro Bertemes Filho
Abstract:Continuous glucose monitoring devices allow diabetes condition management. However, when limited data is available, one option is to increase their size by generating synthetic samples. From a homemade wearable prototype was created a real dataset with 18 instances and 53 attributes that capture characteristics of capillary and venous blood glucose, oxygen concentration, pulse rate, skin temperature, and 24 modules and 24 phases related to bio-impedance. The objective of this article is to generate synthetic d… Show more
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