Predicting Unplanned Readmissions with Highly Unstructured Data
Table 4: Precision and recall by class
['[BOLD] Model', '[BOLD] Prec. 0', '[BOLD] Rec. 0', '[BOLD] Prec. 1', '[BOLD] Rec. 1']
We trained the LSTM model for 6 epochs. The baseline was trained for 8 epochs. On each training we test the model after one epoch on the validation set and we chose the one that performed the best according to the AUROC value. We also tried to do oversampling of the positive values till we reach 20% on the training set but it obtained worse results compared with no oversampling. Although our AUROC (0.76) is comparable with that of similar work We note that Rajkomar et al. On the other hand, the AUROC achieved by our model is above the LACE approximated AUROC performance of 0.72 Improving the recall of our method is part of our future work.