An Artificial-Intelligence- and Telemedicine-Based Screening Tool to Identify Glaucoma Suspects from Color Fundus Imaging

<table class="table-group" id="tab1"><tr><td><table class="table"><tr><td class="thead-hr" colspan="5"><hr/></td></tr><tr class="thead"><td class="align_left">Category (manually graded for vertical cup/disc ratio)</td><td class="align_center">AREDS</td><td class="align_center">SIMES</td><td class="align_center">RIM-ONE1</td><td class="align_center">Total</td></tr><tr><td class="thead-hr" colspan="5"><hr/></td></tr><tr><td class="align_left">≤0.5</td><td class="align_center">462</td><td class="align_center">253</td><td class="align_center">342</td><td class="align_center">1057</td></tr><tr><td class="align_left">Above 0.5</td><td class="align_center">131</td><td class="align_center">243</td><td class="align_center">115</td><td class="align_center">489</td></tr><tr class="table-tr"><td colspan="5"><hr class="tbody-hr"/></td></tr></table></td></tr></table>

<div>Number of images taken from AREDS, SIMES, and RIM-ONE1. The table shows the various groups to which the images belong based on their graded cup/disc ratios.</div>

Journal of Ophthalmology

tab1

Table 1

Table 1: An Artificial-Intelligence- and Telemedicine-Based Screening Tool to Identify Glaucoma Suspects from Color Fundus Imaging 