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SrijanShovit / HealthLearning

A repo comprising of various Machine Learning and Deep Learning projects in healthcare domain.
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Cataract Eye Disease Prediction #133

Closed saikrishna823 closed 2 weeks ago

saikrishna823 commented 1 month ago

Is your feature request related to a problem? Please describe.

Dataset:https://www.kaggle.com/datasets/andrewmvd/ocular-disease-recognition-odir5k The above dataset can used to identify for lot of eye disease.But I will be focusing on cataract disease.As we all know that cataract is one of the eye disease that usually occurs to ageing people .It leads to clouding of the

Describe the solution you'd like

So to identify this I will be designing a deep learning model that can identify the disease.First I will construct a CNN model ,then I will use some pretrained models like Resnet,VGG for better performance.I will be using accuracy, precision as evaluation metrics.

Describe alternatives you've considered

No response

Additional context

No response

Code of Conduct

github-actions[bot] commented 1 month ago

Congratulations, @saikrishna823! 🎉 Thank you for creating your issue. Your contribution is greatly appreciated and we look forward to working with you to resolve the issue. Keep up the great work!

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SrijanShovit commented 1 month ago

I need a model less than 5 MB. So what would be the plan?

saikrishna823 commented 1 month ago

I will use pretrained models like MobileNetV2 , Efficient Net,which are more performant and less in size.

github-actions[bot] commented 3 weeks ago

This issue has been automatically closed because it has been inactive for more than 7 days. If you believe this is still relevant, feel free to reopen it or create a new one. Thank you!

SrijanShovit commented 3 weeks ago

@saikrishna823 I hope you are aware of the flows of an ML project at my repo.

github-actions[bot] commented 2 weeks ago

This issue has been automatically closed because it has been inactive for more than 7 days. If you believe this is still relevant, feel free to reopen it or create a new one. Thank you!