Table 3.

Forecasting Errors^* across Regions and Patient Groups Using Linear Relevance Vector Machine Regression with Measurement Features Augmented with Convolutional Neural Network Features

Diagnosis	Global Mean	Temporal	Superior	Nasal	Inferior
Healthy
MAE	1.10 (0.60)	0.97 (0.91)	3.28 (2.13)	1.26 (1.44)	1.72 (1.01)
MRE	1.22 (0.69)	1.76 (1.68)	2.91 (2.05)	1.90 (2.26)	1.42 (0.85)
Suspects
MAE	1.79 (173)	2.18 (2.60)	2.77 (2.35)	2.39 (2.11)	2.88 (2.36)
MRE	2.19 (2.11)	3.55 (3.92)	2.83 (2.52)	3.75 (3.49)	2.85 (2.34)
Glaucoma
MAE	1.87 (1.85)	3.01 (2.83)	2.59 (2.31)	2.83 (2.29)	3.33 (2.54)
MRE	2.73 (2.81)	5.34 (4.26)	3.14 (2.57)	4.34 (3.50)	4.42 (3.71)
All
MAE	1.81 (1.77)	2.44 (2.68)	2.69 (2.33)	2.56 (2.20)	3.06 (2.45)
MRE	2.44 (2.47)	4.36 (4.57)	2.98 (2.59)	4.01 (3.58)	3.58 (3.30)

MAE = mean absolute error; MRE = mean relative error.

Data are mean (standard deviation).

^*MAE in micrometers and MRE in percent.