Examples of misclassified images of papilledema severity by the Deep Learning System

The study's objective is to evaluate the performance of a deep
learning system (DLS) in classifying the severity of papilledema
associated with increased intracranial pressure, on standard retinal
fundus photographs. A DLS was trained to automatically classify
papilledema severity in 965 patients (2103 mydriatic fundus photographs),
representing a multiethnic cohort of patients with confirmed elevated
intracranial pressure. Training was performed on 1052 photographs with
mild/moderate papilledema (MP) and 1051 photographs with severe
papilledema (SP) classified by a panel of experts, and the performance of
the DLS was tested in 111 patients (214 photographs, 92 with MP
and 122 with SP). In this dataset, we provide illustrative examples of
misclassified images by the DLS, two examples of images wrongly classified
as moderate papilledema instead of severe (figure 1A and 1B), and two
examples of images wrongly classified as severe papilledema instead of
moderate (figure 2A and 2B). Unsurprisingly, DLS errors occurred more
often in patients with moderate papilledema (Frisén 3 severity), a
situation already encountered in clinical studies.