| IDF | International Diabetes Federation |
| T1D | Type 1 diabetes |
| T2D | Type 2 diabetes |
| GDM | Gestational diabetes |
| CHD | Coronary heart disease |
| PAD | Peripheral arterial disease |
| AI | Artificial intelligence |
| ML | Machine learning |
| ECG | Electrocardiography |
| LapSVM | Laplacian support vector machine |
| SVM | Support vector machine |
| DT | Decision Tree |
| LR | Logistic regression |
| AdaBoost | Adaptive boosting |
| URL | Uniform resource locator |
| MML | Multi-agent machine learning |
| IP | Internet protocol |
| ANN | Artificial neural networks |
| RA | Regression algorithm |
| SVR | Support vector regression |
| KNN | K-nearest neighbor |
| RF | Random forest |
| Hkmeans | Hierarchical K-means clustering |
| CGM | Continuous glucose monitoring |
| PH | Prediction horizons |
| PSO | Particle swarm optimization |
| EE | Energy expenditure |
| DR | Diabetic retinopathy |
| RDR | Referable diabetic retinopathy |
| NB | Naive bayes |
| CNN | Convolutional neural networks |
| GBDT | Gradient-boosting decision tree |
| RNN | Recurrent neural network |
| AP | Artificial pancreas |