Table 1.

AUC-ROC of applying the trained LSTM, neural network and ElasticNet models to the training and testing sets. 10-fold cross-validation was applied, and the mean AUC across all folds is presented. Number of Samples denotes the available number of training and testing records as the number of days included in the analysis increases (note the drop in the number of records is due to death or discharge).

Number of Days	Number of Samples RNN (LSTM Model) Neural Network ElasticNet Model
	Training	Testing	Training AUC	Testing AUC	Training AUC	Testing AUC	Training AUC	Testing AUC
1	459	116	0.84	0.78	0.80	0.70	0.86	0.71
2	458	115	0.88	0.82	0.84	0.76	0.92	0.76
3	456	115	0.89	0.85	0.86	0.79	0.94	0.80
4	453	114	0.91	0.86	0.87	0.81	0.95	0.81
5	447	112	0.92	0.87	0.88	0.81	0.97	0.84
6	440	110	0.92	0.87	0.89	0.82	0.98	0.83
7	434	109	0.93	0.88	0.89	0.83	0.98	0.81
8	427	107	0.93	0.89	0.90	0.84	0.98	0.80
9	414	104	0.93	0.89	0.91	0.83	0.98	0.79
10	400	100	0.94	0.89	0.91	0.83	0.98	0.78
11	376	94	0.94	0.89	0.92	0.84	0.99	0.78
12	354	89	0.94	0.89	0.92	0.84	0.98	0.75
13	321	81	0.93	0.89	0.90	0.83	0.98	0.74
14	298	75	0.92	0.88	0.89	0.83	0.98	0.74
15	275	70	0.92	0.86	0.88	0.80	0.98	0.72