Using Machine Learning to Investigate Predictors of Fasting Blood Glucose: Insights into Circadian Timing and Age Interactions

arXiv:2609.32386 · cs.LG · Submitted 2026-09-26 · Read on arXiv

cs.LG

Submitted: 2026-09-26

Updated: 2026-09-26

Code: https://github.com/Vitashka1995/circadian-glucose-prediction

Terminology

• Robustness — 16× in this paper · explained in 5 episodes
• Calibration — 15× in this paper · explained in 7 episodes
• Feature Selection — 13× in this paper · explained in 4 episodes
• SHAP values — 9× in this paper · explained in 2 episodes
• Feature Engineering — 6× in this paper · explained in 3 episodes
• alpha — 6× in this paper · explained in 1 episode
• Interpretability — 5× in this paper · explained in 15 episodes
• Pruning — 5× in this paper · explained in 4 episodes
• Ablation — 4× in this paper · explained in 1 episode
• Accuracy — 4× in this paper · explained in 1 episode
• Clustering — 3× in this paper · explained in 2 episodes
• Alignment — 2× in this paper · explained in 1 episode
• Benchmark — 2× in this paper · explained in 2 episodes
• Generalizability — 2× in this paper · explained in 6 episodes
• National Health and Nutrition Examination Survey — 2× in this paper
• Parsimony — 2× in this paper · explained in 2 episodes
• Causal Inference — 1× in this paper · explained in 4 episodes
• Centers for Disease Control and Prevention — 1× in this paper
• Consistency — 1× in this paper · explained in 3 episodes
• External Validation — 1× in this paper · explained in 2 episodes
• Generalization — 1× in this paper · explained in 13 episodes
• Information Leakage — 1× in this paper · explained in 2 episodes
• Systematic Bias — 1× in this paper · explained in 3 episodes
• Unified Framework — 1× in this paper · explained in 5 episodes

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