Table 4.

Performance of the automated scoring system (A): Full dataset (pre-modification: n = 2,646; post-modification n = 2,510); (B): Small dataset with only those feet which were scored by both algorithms (AUT1 and AUT2), n = 1,135.

(A)		Sensitivity	Specificity	PPV	NPV	Accuracy
Score 0	AUT1	0.07 ± 0.02	0.99 ± 0.00	0.77 ± 0.08	0.89 ± 0.01	0.89 ± 0.01
	AUT2	0.24 ± 0.04	0.99 ± 0.00	0.71 ± 0.07	0.96 ± 0.00	0.96 ± 0.00
Score 1	AUT1	0.59 ± 0.04	0.82 ± 0.01	0.19 ± 0.02	0.97 ± 0.00	0.81 ± 0.01
	AUT2	0.30 ± 0.02	0.96 ± 0.00	0.73 ± 0.03	0.80 ± 0.01	0.79 ± 0.01
Score 2	AUT1	0.78 ± 0.01	0.55 ± 0.01	0.55 ± 0.01	0.78 ± 0.01	0.65 ± 0.01
	AUT2	0.89 ± 0.01	0.54 ± 0.01	0.62 ± 0.01	0.85 ± 0.01	0.69 ± 0.01
Score 3	AUT1	0.63 ± 0.02	0.85 ± 0.01	0.59 ± 0.02	0.87 ± 0.01	0.79 ± 0.01
	AUT2	0.67 ± 0.02	0.94 ± 0.01	0.75 ± 0.02	0.91 ± 0.01	0.88 ± 0.01
Score 4	AUT1	0.79 ± 0.08	0.95 ± 0.00	0.13 ± 0.03	0.99 ± 0.00	0.94 ± 0.01
	AUT2	0.60 ± 0.09	0.99 ± 0.00	0.35 ± 0.07	0.99 ± 0.00	0.98 ± 0.00
(B)		Sensitivity	Specificity	PPV	NPV	Accuracy
Score 0	AUT1	0.07 ± 0.02	0.99 ± 0.00	0.64 ± 0.13	0.89 ± 0.01	0.89 ± 0.01
	AUT2	0.23 ± 0.05	0.99 ± 0.00	0.64 ± 0.10	0.95 ± 0.01	0.94 ± 0.01
Score 1	AUT1	0.18 ± 0.02	0.95 ± 0.01	0.57 ± 0.05	0.77 ± 0.01	0.75 ± 0.01
	AUT2	0.34 ± 0.03	0.96 ± 0.01	0.75 ± 0.04	0.80 ± 0.01	0.79 ± 0.01
Score 2	AUT1	0.86 ± 0.02	0.46 ± 0.02	0.54 ± 0.02	0.82 ± 0.02	0.63 ± 0.01
	AUT2	0.90 ± 0.01	0.51 ± 0.02	0.62 ± 0.02	0.86 ± 0.02	0.69 ± 0.01
Score 3	AUT1	0.61 ± 0.03	0.90 ± 0.01	0.60 ± 0.03	0.90 ± 0.01	0.84 ± 0.01
	AUT2	0.58 ± 0.03	0.95 ± 0.01	0.72 ± 0.03	0.91 ± 0.01	0.88 ± 0.01
Score 4	AUT1	0.55 ± 0.15	0.97 ± 0.01	0.15 ± 0.06	0.99 ± 0.00	0.97 ± 0.01
	AUT2	0.40 ± 0.15	0.99 ± 0.00	0.21 ± 0.0	0.99 ± 0.00	0.98 ± 0.00

AUT1: algorithm for automated detection pre-modification; AUT2: algorithm for automated detection post-modification; PPV: positive predicted value; NPV: negative predictive value; data is presented ± standard error; dark gray indicating an increase; light gray indicating a decrease.