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Abstract Fungal keratitis is a corneal infection caused by filamentous fungi or yeasts. It can progress rapidly and, if not diagnosed and treated promptly, may lead to irreversible visual impairment or blindness. In this study, we developed CSwinFK, a classification model for distinguishing fungal keratitis from negative cases using in vivo confocal microscopy images. This model is based on a novel bidirectional cross-attention fusion of the CNN architecture and Swin Transformer.
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