GENERATION OF INDIVIDUALIZED SYNTHETIC DATA FOR AUGMENTATION OF THE TYPE 1 DIABETES DATA SETS USING DEEP LEARNING MODELS

Generation of Individualized Synthetic Data for Augmentation of the Type 1 Diabetes Data Sets Using Deep Learning Models

In this paper, we present a methodology based on generative adversarial network architecture to generate synthetic data sets with the intention of augmenting continuous glucose monitor data from individual patients.We use these synthetic data with the aim of improving the overall performance of prediction models based on machine learning techniques

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Childhood trauma subtypes may influence the pattern of substance use and preferential substance in men with alcohol and/or crack-copyright addiction

Objective: To compare the prevalence and subtypes of childhood maltreatment (CM) between individuals with and without substance use disorder (SUD) and investigate the influence of different traumas on the preferential use of substances and the Comics Statues severity of dependence.Methods: The sample consisted of 1,040 men with SUD (alcohol users [

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