• PERAVALI SRI VIJAYA
• Mr.VANKAYALA ANIL SANTOSH
• ATHILI VENKATA RAJU

The situation with the COVID-19 pandemic has greatly affected the whole world and the occurrence of the respiratory complications that led to it has been a major threat, especially in the developing nations such as the case of India. The diagnosis should be timely and accurate to prevent the spread and start the treatment in time. In this project, a deep learning-based classification model, which represents COVID-19 by the images of chest X-rays, will be produced. The system utilizes the capabilities of Convolutional Neural Networks (CNNs) with the help of the Keras framework that can train neural networks to differentiate between normal, pneumonia, and COVID-19 affected lungs. The model fits in a Graphical User Interface (GUI) that enables health providers to upload X-ray images and get real-time result as predictions of diagnostic occurrences. It is a resource-intensive environment, which uses accuracy, usability, and speed to make the system very useful.

Convolutional Neural Networks, COVID-19, Graphical User Interface (GUI), Keras Framework, X-ray images, Deep Learning.

"A Machine Learning Approach for Automation of Resume Recommendation System", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.12, Issue 7, page no.b120-b130, July-2025, Available :http://www.jetir.org/papers/JETIR2507113.pdf

"A Machine Learning Approach for Automation of Resume Recommendation System", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.12, Issue 7, page no. ppb120-b130, July-2025, Available at : http://www.jetir.org/papers/JETIR2507113.pdf