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This can be a proof of idea research which used a convenience sample of transnasal, versatile, distal-chip laryngoscopy photos from customers post-extubation when you look at the intensive treatment product. After manually annotating images at the pixel-level, we applied a CNN-based way for analysis of granulomas and ulcerations to test potential machine-learning methods for laryngoscopy evaluation. A total of 127 pictures from 25 clients had been manually annotated for existence and form
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