Abstract- Diagnosis is a critical preventive step in Coronavirus research which has similar manifestations with other types of pneumonia and lung cancer. X-rays play an important role in that direction. However, processing chest X-ray images and using them to accurately diagnose lung ailments is a computationally expensive task. Machine Learning techniques have the potential to overcome this challenge. This study proposed a CNN model to automatically detect COVID-19, pneumonia and lung cancer patients from digital chest x‐ray images using deep convolution of neural networks. Here we use X-ray images which is pre-processed and given as input to the pre-trained model. In this model, the feature extraction process takes place in both convolutional and pooling layers. The classification process occurs in fully connected layer. The proposed model InceptionV3 performs with an accuracy of 88% and a precision of 92%. This model gives the F1-score of 88.0.
Keywords- Covid-19, Pneumonia, Lung Cancer, Chest X-ray, CNN, Deep Transfer Learning, Lung Ailments detection.

| DOI: 10.17148/IJIREEICE.2022.10559