Racial disparities in continuous glucose monitoring-based 60-min glucose predictions among people with type 1 diabetes

Keyphrases

• Age Data 20%
• Algorithmic Fairness 20%
• Black Participants 60%
• Continuous Glucose Monitoring 100%
• Continuous Glucose Monitoring Data 40%
• Deep Learning Model 20%
• Diabetes Technology 20%
• Divergence 20%
• Fair Prediction 20%
• Glucose Prediction 100%
• Health Disparities 20%
• Health Research 20%
• Learning Model 20%
• Linear Mixed Model 20%
• Long Short-term Memory 20%
• Machine Learning Models 20%
• Medical Research 20%
• Non-Hispanic White 20%
• Prediction Model 20%
• Racial Composition 40%
• Racial Disparities 100%
• Root Mean Square Error 100%
• Slope Difference 20%
• Statistically Significant Difference 20%
• Training Data 40%
• Training Sample Size 20%
• Transfer Learning 60%
• Type 1 Diabetes Mellitus (T1DM) 100%
• Type I Diabetes 100%
• White Patients 20%
• White Population 20%

Medicine and Dentistry

• Deep Learning Model 16%
• Diabetes 16%
• Glucose 100%
• Insulin Dependent Diabetes Mellitus 100%
• Prediction Model 16%
• Racial Disparity 100%
• Short Term Memory 16%
• Transfer of Learning 50%
• White Population 16%

Psychology

• Glucose 100%
• Learning Model 33%
• Short-Term Memory 16%
• Transfer of Learning 50%
• United States of America 16%