You can deploy this model and start earning money today!

Ahmed-Selem/
Shifaa-COVID-Chest-Xray-ResNet50

Name: Shifaa-COVID-Chest-Xray-ResNet50
Availability: InStock

Views

No views yet

COVID-19 Chest X-ray Model

Model Information:

Architecture: ResNet50
Task: Multi-class classification (4 conditions)
Dataset: COVID-19 Radiography Database
Input Size: 224×224 RGB images

Classes:

COVID
Lung_Opacity
Normal
Viral Pneumonia

Performance Metrics:

Accuracy: 91.6%
Precision: 0.92
Recall: 0.91
F1-Score: 0.91

Usage:

python

from shifaa.vision import VisionModelFactory

model = VisionModelFactory.create_model(
    model_type="classification",
    model_name="Chest_COVID"
)

result = model.run("chest_xray.jpg", show_image=True)
print(f"Diagnosis: {result['predicted_class']}")
print(f"Confidence: {result['confidence']:.2f}%")

Confusion Matrix:

Preprocessing:

Resize to 224×224
Random horizontal flip
Random rotation ±10°
Color jitter (brightness & contrast)
ImageNet normalization

Training Details:

Loss Function: CrossEntropyLoss (with class weights)
Optimizer: Adam (lr=0.0005)
Epochs: 30
Batch Size: 32

Ahmed-Selem/Shifaa-COVID-Chest-Xray-ResNet50

Ahmed-Selem/
Shifaa-COVID-Chest-Xray-ResNet50