Automated classifiers for early detection and diagnosis of retinopathy in diabetic eyes

BMC Bioinformatics

Table 3 Test classification performance results obtained in Test 1 after using the total reflectance as an input feature

TR vs. FD	RNFL (eye/scans)	GCL + IPL (eye/scans)	INL (eye/scans)	OPL (eye/scans)	ONL + IS (eye/scans)	OS (eye/scans)	RPE (eye/scans)
TP	48/288	49/294	48/288	48/288	48/288	50/300	51/306
FN	6/36	5/30	6/36	6/36	6/36	4/24	3/18
TN	10/60	35/210	23/138	37/222	9/54	9/54	11/66
FP	33/198	8/48	20/120	6/36	34/204	34/204	32/192
PPV	0.59	0.86	0.71	0.89	0.59	0.60	0.61
Sensitivity	0.89	0.91*	0.89	0.89*	0.89	0.93	0.94
Specificity	0.23	0.81*	0.53	0.86*	0.21	0.21	0.26

*denotes the intraretinal layer for which the sensitivity, specificity and PPV are greater than 80%.
Sensitivity, specificity, predictive values (TP, FN, TN, FP) and positive predictive values (PPV) obtained when training the Bayesian radial basis function network using the total reflectance (TR) and fractal dimension (FD) as the input and target features, respectively.

ISSN: 1471-2105