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Feature Description

• Deep learning techniques are leveraged in pseudo-papilledema detection by training convolutional neural networks (CNNs) on large datasets of retinal images to differentiate between true papilledema and pseudo-papilledema.
• These models can automatically extract relevant features from the images, leading to high accuracy in identifying subtle differences that might be challenging for human observers.
• This approach improves diagnostic accuracy, reduces the need for invasive procedures, and supports ophthalmologists in making timely and precise decisions.

@TAHIR0110, @Avdhesh-Varshney, could you please assign me this issue under GSSOC'24

Use Case

Supports ophthalmologists in making timely and precise decisions.

Benefits

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Priority

High

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