Table 4.

Model performance for external validation dataset (sensitivity is maximized while specificity is closest to 0.5 but not less)

MODELS	AUC	Threshold	Sensitivity	Specificity
THEATER BBN	0.68 [0.58,0.78]	0.51 [0.29,0.58]	0.68 [0.41,0.88]	0.63 [0.51,0.86]
THEATER TRMS	0.72 [0.63,0.81]	1	0.74 [0.64,0.85]	0.69 [0.55,0.82]
THEATER BBN + TRMS	0.71 [0.63,0.80]	0.60 [0.49,0.74]	0.80 [0.69,0.90]	0.59 [0.51,0.69]
THEATER BBN + TRMNS	0.77 [0.69,0.84]	0.12 [0.12,0,12]	0.74 [0.64,0.85]	0.69 [0.55,0.82]
MEDCEN BBN	0.67 [0.57,0.78]	0.48 [0.25,0.50]	0.71 [0.54,0.87]	0.57 [0.51,0.69]
MEDCEN TRMS	0.71 [0.63,0.81]	1	0.74 [0.63,0.87]	0.68 [0.53,0.81]
MEDCEN BBN + TRMS	0.70 [0.61,0.80]	0.56 [0.49,0.75]	0.80 [0.69,0.90]	0.55 [0.51,0.65]
MEDCEN BBN + TRMNS	0.76 [0.68,0.85]	0.12 [0.12,0.12]	0.74 [0.63,0.87]	0.68 [0.53,0.81]

BBN = Bayesian Belief Network (produces a probability for having IFI)

TRMS = Two-rule Model Satisified (assigns 1 if satisfied, and 0 otherwise)

BBN + TRMS = Bayesian Belief Network plus Two-rule Model Satisfied (assigns 1 if TRM is satisfied, otherwise BBN produces a probability for having IFI)

BBN + TRMNS = Bayesian Belief Network plus Two-rule Model Not Satisfied (assigns 0 if TRM is not satisfied, otherwise BBN produces a probability for having IFI)