This is part of my internship at Endimension Technology, IIT Bombay.
PyTorch implementation of CheXNet: Radiologist level pneumonia detection using deep learning based on this implementation.
You can run the complete notebook on Kaggle -> CheXNet-PyTorch
Batch size | Learning Rate | Epochs | Time |
---|---|---|---|
64 | 0.01 | 20 | 2 hrs |
Pathology | AUROC |
---|---|
Atelectasis | 0.735 |
Cardiomegaly | 0.882 |
Effusion | 0.82 |
Infiltration | 0.673 |
Mass | 0.788 |
Nodule | 0.728 |
Pneumonia | 0.647 |
Pneumothorax | 0.799 |
Consolidation | 0.689 |
Edema | 0.832 |
Emphysema | 0.858 |
Fibrosis | 0.77 |
Pleural_Thickening | 0.719 |
Hernia | 0.846 |