Table 1.
LSTM, LR, and XGBoost performance comparison for (a) AKI (b) prediction.
| Model | Accuracy | Precision | Recall | AUROC | AUPRC |
|---|---|---|---|---|---|
|
| |||||
| LSTM | 0.854 | 0.628 | 0.673 | 0.873 | 0.699 |
| LR | 0.816 | 0.532 | 0.618 | 0.832 | 0.566 |
| XGBoost | 0.831 | 0.571 | 0.638 | 0.855 | 0.658 |
|
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| (a) | |||||
|
| |||||
| Model | Accuracy | Precision | Recall | AUROC | AUPRC |
|
| |||||
| LSTM | 0.992 | 0.595 | 0.537 | 0.985 | 0.603 |
| LR | 0.985 | 0.226 | 0.135 | 0.906 | 0.213 |
| XGBoost | 0.991 | 0.538 | 0.512 | 0.967 | 0.522 |
|
| |||||
| (b) | |||||