Table 2.

Accuracy at identifying whether ongoing cases will finish by 15:00. MANN, modular artificial neural network.

Model	True positive	True negative	False positive	False negative	Sensitivity (%)	Specificity (%)	Precision (%)	Accuracy (%)
Prediction time: 11:00
MANN	156	1711	25	114	57.78	98.56	86.19	93.07
Bayesian	140	1682	54	130	51.85	96.89	72.16	90.83
Naïve	152	1672	64	118	56.30	96.31	70.37	90.93
Prediction time: 12:00
MANN	250	1464	48	121	67.39	96.83	83.89	91.02
Bayesian	216	1427	85	155	58.22	94.38	71.76	87.25
naïve	225	1404	108	146	60.65	92.86	67.57	86.51
Prediction time: 13:00
MANN	447	1126	71	147	75.25	94.07	86.29	87.83
Bayesian	422	1062	135	172	71.04	88.72	75.76	82.86
naïve	413	1037	160	181	69.53	86.63	72.08	80.96
Prediction time: 14:00
MANN	853	698	79	107	88.85	89.83	91.52	89.29
Bayesian	840	543	234	120	87.50	69.88	78.21	79.62
naïve	743	618	159	217	77.40	79.54	82.37	78.35