GitHub topics: aptos2019
SuryaVamsi-P/Diabetic-Retinopathy-Detection-with-ResNet50
Built an end-to-end deep learning pipeline using ResNet-50 to classify retinal images into five stages of Diabetic Retinopathy. Applied transfer learning, image preprocessing, and AUC-based evaluation on the APTOS 2019 Kaggle dataset, achieving a 94% validation AUC—offering real-world potential in clinical diagnosis automation.
Language: Python - Size: 2.15 MB - Last synced at: 20 days ago - Pushed at: 2 months ago - Stars: 0 - Forks: 0
Related Keywords
aptos2019
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auc-evaluation
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clinical-decision-support
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cnn-model
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computer-vision
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data-augmentation
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deep-learning
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diabetic-retinopathy
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early-detection
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healthcare-ai
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image-classification
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keras
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medical-diagnosis
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medical-imaging
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multi-class-classification
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optical-imaging
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resnet50
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retinal-image-analysis
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tensorflow
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transfer-learning
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