Table 1:

Predictive model accuracy for the three different steps. M1: A model trained without weights on each class. M2: A model trained with weights on each class to mitigate the effect of the imbalance of the distribution of classes.

Remission Prediction	Step 1		Step 2		Step 3
	M1	M2	M1	M2	M1	M2
Accuracy	0.680 (0.034)	0.66 (0.024)	0.709 (0.051)	0.713 (0.025)	0.837 (0.047)	0.846 (0.071)
AUC	0.735 (0.031)	0.731 (0.032)	0.770 (0.041)	0.775 (0.038)	0.866 (0.117)	0.842 (0.105)
Sensitivity	0.620 (0.037)	0.65 (0.032)	0.572 (0.060)	0.743 (0.06)	0.360 (0.185)	0.69 (0.12)
Specificity	0.737 (0.036)	0.67 (0.023)	0.815 (0.055)	0.69 (0.034)	0.976 (0.030).	0.888 (0.083)
PPV	0.695 (0.040)	0.655 (0.024)	0.706 (0.079)	0.649 (0.021)	0.667 (0.365)	0.67 (0.189)
NPV	0.664 (0.025)	0.666 (0.025)	0.727 (0.036)	0.779 (0.038)	0.660 (0.185)	0.911 (0.03)

AUC: Area under the Curve, PPV: Positive predictive value, NPV: Negative predictive value