Arko007/Cataract-Detection-CNN

title: Cataract Detection - Overfitted Beast (Data Leakage Demo) emoji: 👁️ colorFrom: red colorTo: orange sdk: gradio sdkversion: 4.44.0 appfile: app.py pinned: false license: apache-2.0 ---

🚨 Cataract Detection Model - OVERFITTED BEAST 🚨

⚠️ WARNING: This model has DATA LEAKAGE and should NOT be used in production!

This model was intentionally trained with data leakage to demonstrate the difference between:

• —Fake high performance (0.967% accuracy due to leakage)
• —Real medical AI performance (typically 80-90%)

📊 "Impressive" Results (Due to Leakage):

• —Test Accuracy: 0.967 🎭 (fake!)
• —Precision: 0.957
• —Recall: 0.976
• —AUC: 0.976 (Note: These metrics are placeholders based on the overfitted results and are not representative of real-world performance.)

🕵️ How the Leakage Occurred:

1. 1.Same base images were augmented multiple times
2. 2.Augmented versions appeared in both training and validation sets
3. 3.Model "cheated" by recognizing the same underlying images
4. 4.Inflated performance that doesn't generalize to real-world data

🧪 What This Model Actually Learned:

• —Memorized specific image artifacts
• —Recognized augmentation patterns
• —Found shortcuts instead of medical features
• —NOT real cataract detection ability

🎯 Educational Purpose:

This demonstrates why proper data splitting is crucial in medical AI:

• —Split BEFORE augmentation
• —Ensure no patient/image appears in multiple splits
• —Realistic medical AI achieves 80-90% accuracy

🔬 Try It Out:

Test this model to see how it performs on truly unseen cataract images!

Built with: Custom EfficientNet architecture, TensorFlow, AdamW optimizer

Note: Tomorrow we'll upload the corrected version with proper data splits! 🏥✅