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Detect Retina Diseases with Deep Learning

Worldwide there are about 1 billion people affected by some kind of vision impairment. Many suffer from eye diseases like cataract, glaucoma or retina diseases.

We have trained a deep learning model to detect these three different eye diseases with a very small dataset of about 300 image files. The data comes from a kaggle competition and can be downloaded here. This is a very small dataset for training a deep neural net. Therefore we have used a technology called transfer learning to improve training time and accuracy for small training datasets.

Use of Transfer Learning

Though we have very less training examples to train a deep neurol net, we have achieved good results by use of a technique called Transfer Learning. This means, we use a pretrained model like ResNet34, cut the last layer, add a new dense layer with 4 output nodes and only train the last layer.

With this process our model can profit from the pretrained basic layers and we can achieve better results in a shorter periode of time.

Please be aware of the fact, that this model is used for demonstrations only. It's not meant for real diagnosis of eye diseases. If you think you suffer from any vision impairment, consult your ophthalmologist!

If you are more interested in how we implemented the deep learning model have a look at the jupyter notebook in the repository.
If you are curious on how to host a deep learning model see our blog post on medium: put-deep-learning-image-classifier-in-action

Try to analyze an Image of the Retina

Just click on select and select an image of the retina. Click on Analyze.

If you need some example images of eye diseases to test our mordel, search for terms like "image retina disease": duckduckgo.com

Chosen Image

This is a Project for demonstrations Purposes of we-make.ai | Your AI-Consultants

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our blog in german: www.kuenstliche-intelligenz-in-a-nutshell

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