In this project, we develop a convolutional neural network (CNN) model for classifying chest X-rays as either normal or showing signs of pneumonia. The model was trained on a dataset of over 5,863 X-ray images, and achieved an accuracy of 89% on the test set. The architecture of the model consists of multiple convolutional layers, followed by max pooling and dense layers.
dataset we used Chest X-Ray Images (Pneumonia)
full project in details in the documentation
✔️Classify the x-ray imagest to two category
- Pneumonia
- Normal
✔️Used All evaluation metrics
The following tools were used in this project:
- tensorflow==2.12.0
- tqdm
- scikit-learn
- matplotlib
- numpy
- pandas
- pickle
- cv2
- CNN
- Tensorflow, keras
- Jupyter notebook
- deep learning
-
Romani
-
Ahmed Mohamed Ali
-
Reham Mustafa
-
Sara Reda Moatamed
-
Rana Hasan Badrawy
-
Rawan Abdel-Aziz Ahmed
