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@@ -35,10 +35,8 @@ To obtain optimal predictions, it is recommended to provide this model with stan
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  <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
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- The pretrained model provides glaucoma classification functionality solely based on analysis of retinal fundus images.
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- You may directly utilize the raw model without modification to categorize fundus images as either glaucoma or non-glaucoma.
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- This model is specialized in extracting discriminative features from fundus images to identify glaucoma manifestations.
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- However, to achieve optimal performance, it is highly recommended to fine-tune the model on a representative fundus image dataset prior to deployment in real-world applications.
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  ## Bias, Risks, and Limitations
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  <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
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+ his pretrained model enables semantic segmentation of key anatomical structures, namely, the optic disc and optic cup, in retinal fundus images.
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+ It takes fundus images as input and outputs the segmentation results.
 
 
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  ## Bias, Risks, and Limitations
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