ItemArticle

Deep CP-CXR: A Deep Learning Model for Classification of Covid-19 and Pneumonia Disease Using Chest X-Ray Images

Title
Deep CP-CXR: A Deep Learning Model for Classification of Covid-19 and Pneumonia Disease Using Chest X-Ray Images
Creator
Singh, Kuljeet; Gaur, Anubha; Kumar, Sachin; Shastri, Sourabh; Mansotra, Vibhakar
Description
The global spread of the Coronavirus has caused a disastrous effect, affecting millions of people and making it crucial to take action. Numerous experts have worked extensively to create viable vaccines in the fight against this infectious disease. The current study offers hope by suggesting a deep learning model, Deep CP-CXR, for determining patients with Covid-19 and pneumonia. Our study encompasses two significant investigations. First, we used images from chest X-rays for binary classification to distinguish Covid-19-diagnosed patients from normal patients. Second, using chest X-ray images, we expanded the study to include several groups, such as pneumonia, Covid-19, and normal instances. The results of our studies were extremely promising. The binary classification achieved a remarkable average accuracy of 100%, allowing for accurate classification between Covid-19 patients and normal cases. In addition, the multiple-category classification was able to distinguish between Covid-19, pneumonia, and normal individuals with a remarkable average accuracy of 98.57%. These astounding findings lead us to conclude that the Deep CP-CXR method weve suggested for classifying Covid-19 and pneumonia patients enables medical professionals to perform it accurately. Healthcare providers worldwide will benefit significantly from this development since it has the potential to enhance both the detection and treatment of these ailments. The proposed deep learning approach improves the speed and precision in classifying the disease with which doctors can diagnose and treat their patients effectively. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2025.
Source
Annals of Data Science;
Date
01-01-2025
Publisher
Springer Science and Business Media Deutschland GmbH
Subject
Chest X-ray; Classification; Covid-19; Deep learning; Pneumonia
Coverage
Singh K., Department of Computer Science, School of Sciences, Christ University, Delhi-NCR, India; Gaur A., Information Technology, KIET Group of Institutions, Ghaziabad, India; Kumar S., Department of Computer Science & IT, University of Jammu, Jammu & Kashmir, Jammu, India; Shastri S., Department of Computer Science & IT, University of Jammu, Jammu & Kashmir, Jammu, India; Mansotra V., Department of Computer Science & IT, University of Jammu, Jammu & Kashmir, Jammu, India
Rights
Restricted Access; Hardcopy may be available in the library
Relation
ISSN: 21985804;
Format
online
Language
English
Type
Article

Citation

Singh, Kuljeet; Gaur, Anubha; Kumar, Sachin; Shastri, Sourabh; Mansotra, Vibhakar, “Deep CP-CXR: A Deep Learning Model for Classification of Covid-19 and Pneumonia Disease Using Chest X-Ray Images,” CHRIST (Deemed To Be University) Institutional Repository, accessed June 20, 2026, https://archives.christuniversity.in/items/show/22075.

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