Table 8.
Medicine
| Title | The use of data mining methods for the prediction of dementia: evidence from the english longitudinal study of aging |
| Description | Classify dementia on imbalanced data, maximum cardinality of feature is 50, compare CatBoost to other classifiers |
| Performance metric | Normalized Gini coefficient |
| Winner | Convolutional neural network |
| Reference | [26] |
| Title | A novel fracture prediction model using machine learning in a community-based cohort |
| Description | Use CatBoost to predict fragility fracture |
| Performance metric | AUC |
| Winner | CatBoost |
| Reference | [24] |
| An efficient novel approach for iris recognition based on stylometric features and machine learning techniques | |
| Description | Use CatBoost after doing feature extraction from image data converted to base-64 encoded data |
| Performance metric | AUC |
| Winner | multiboostAB |
| Reference | [23] |