AI Medical Compendium Journal:
Nutrition & diabetes

Showing 1 to 4 of 4 articles

Optimization of diabetes prediction methods based on combinatorial balancing algorithm.

Nutrition & diabetes
BACKGROUND: Diabetes, as a significant disease affecting public health, requires early detection for effective management and intervention. However, imbalanced datasets pose a challenge to accurate diabetes prediction. This imbalance often results in...

Relationships between minerals' intake and blood homocysteine levels based on three machine learning methods: a large cross-sectional study.

Nutrition & diabetes
BACKGROUND: Blood homocysteine (Hcy) level has become a sensitive indicator in predicting the development of cardiovascular disease. Studies have shown an association between individual mineral intake and blood Hcy levels. The effect of mixed mineral...

Machine learning modeling practices to support the principles of AI and ethics in nutrition research.

Nutrition & diabetes
BACKGROUND: Nutrition research is relying more on artificial intelligence and machine learning models to understand, diagnose, predict, and explain data. While artificial intelligence and machine learning models provide powerful modeling tools, failu...

Identification and epidemiological characterization of Type-2 diabetes sub-population using an unsupervised machine learning approach.

Nutrition & diabetes
BACKGROUND: Studies on Type-2 Diabetes Mellitus (T2DM) have revealed heterogeneous sub-populations in terms of underlying pathologies. However, the identification of sub-populations in epidemiological datasets remains unexplored. We here focus on the...