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@@ -44,11 +44,9 @@ However, to achieve optimal performance, it is highly recommended to fine-tune t
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  <!-- This section is meant to convey both technical and sociotechnical limitations. -->
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- The model is specialized in analyzing retinal fundus images, and is trained exclusively on fundus image datasets to classify images as glaucoma or non-glaucoma.
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- Therefore, to obtain accurate predictions, it is crucial to only input fundus images when using this model.
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- Feeding other types of images may lead to meaningless results.
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- In summary, this model expects fundus images as input for glaucoma classification.
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- For the best performance, please adhere strictly to this input specification.
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  ## How to Get Started with the Model
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  <!-- This section is meant to convey both technical and sociotechnical limitations. -->
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+ The model has undergone specialized training and fine-tuning exclusively using retinal fundus images,
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+ with the objective to perform semantic segmentation of anatomical structures including the optic disc and optic cup.
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+ Therefore, in order to derive optimal segmentation performance, it is imperative to ensure that only fundus images are entered as inputs to this model.
 
 
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  ## How to Get Started with the Model
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