Pneumonia Detection from Chest X-Rays
What it is
A comparative study of deep learning architectures and data balancing techniques for detecting pneumonia in pediatric chest X-rays. It implements multiple Convolutional Neural Network (CNN) models and evaluates them against a dataset with severe class imbalance.
The problem it solves
Addresses the challenge of severe class imbalance in medical datasets which can lead to biased AI models.
What you could use it for
- Automated pneumonia detection in pediatric medical imaging
- Comparative analysis of CNN architectures (ResNet18, VGG16) for medical diagnosis
- Implementing data balancing techniques (upsampling, weighted sampling) in medical AI
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