Medical Image Classification
Overview
Created a deep learning model to classify medical images for early disease detection, focusing on pneumonia identification in chest X-rays.
Methodology
Implemented a Convolutional Neural Network with transfer learning using pre-trained ResNet50 architecture. Applied data augmentation to improve model generalization.
Key Findings
- Achieved 94.7% accuracy in pneumonia detection
- Transfer learning significantly reduced training time and improved performance
- Model showed 92% sensitivity and 96% specificity in clinical validation
Data Visualization
Project Details
Technologies
Dataset
5,863 X-Ray images from Kaggle Pneumonia Detection Challenge
Completed
September 2023
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