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. 2022 Jul 26;12:12745. doi: 10.1038/s41598-022-16980-z

Table 4.

Comparison of classification accuracy using either BAF or OCT images for each of the 4 described methods.

BAF images OCT images p
UP hb 0.614 (CI 0.557–0.672) 0.662 (CI 0.657–0.684) 0.031
P hb 0.785 (CI 0.768–0.810) 0.741 (CI 0.718–0.757) 0.025
UP CNN 0.861 (CI 0.843–0.879) 0.867 (CI 0.853–0.881) 0.652
P CNN 0.880 (CI 0.862–0.896) 0.893 (CI 0.882–0.911) 0.790

The analysis responds to the question “Does UPhb/Phb/UP CNN/P CNN perform better when applied on BAF or OCT images?”. BAF blue autofluorescence, CNN convolutional neural network, OCT optical coherence tomography, P CNN CNN classification of unprocessed images, P hb human-based classification of processed images, UP CNN CNN classification of unprocessed images, UP hb human-based classification of unprocessed images.