Chest X-Ray Images to Differentiate COVID-19 from Pneumonia with Artificial Intelligence Techniques

Algorithm 1

Steps to classify the X-ray images using VGG16.

1: Load images for training, testing, and validation

2: Rescale the images to (224, 224, 3)

3: Normalize the pixel values of the images between 0 and 1

4: Load the pre-trained VGG16 model

5: Freeze the base network

6: Flatten the network

7: Add two dense network layers on top of the base network

8: Split the images, into training, validation, and testing set in the ratio of 70:15:15

9: Extract the feature map, from the images using pre-trained VGG16

10: Set the epoch,

11: Set the counter, i

12: do while

13:  Select the initial hyperparameter values (e.g., learning rate, batch size, etc)

14:  Train the classifier using the training dataset

15:  Evaluate VGG16 performance with the validation data

16: end

17: Choose the best weight matrix that provides minimum validation error rate

18: Compute prediction scores, based on testing samples

19: Classify samples as COVID-19 or pneumonia using

20: Identify the best-trained model using the test images