Ellie190/BCNN-for-Ocular-Disease-Classification
A Bayesian Convolutional Neural Network model for classifying Cataract in Ocular Disease with measurements of uncertainty
This project helps medical professionals, specifically ophthalmologists and diagnosticians, classify ocular disease images to detect cataracts. It takes patient eye images as input and outputs a classification (Cataract or Normal) along with an indication of the model's confidence in its prediction. This ensures more reliable diagnoses by highlighting cases where further review might be needed.
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Use this if you need a reliable automated system to assist in the initial screening or diagnosis of cataracts from eye images, especially when understanding the certainty of the diagnosis is critical.
Not ideal if you are looking for a simple, fast classification without any consideration for the uncertainty or risk associated with misdiagnosis.
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MIT
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Last pushed
Jun 15, 2022
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