ItemArticle

Enhanced Pneumonia Detection from Chest X-rays Using Machine Learning and Deep Neural Architectures

Title
Enhanced Pneumonia Detection from Chest X-rays Using Machine Learning and Deep Neural Architectures
Creator
Upreti, Kamal; Singh, Anju; Singh, Divakar; Shoran, Preety; Shankar, Uma; Yadav, Meenakshi; Jain, Rituraj
Description
Pneumonia is a major worldwide health concern, particularly for vulnerable groups such as babies and the elderly. Despite advances in medical imaging, diagnosing pneumonia using a chest X-ray remains difficult, due to the subtle presentation of symptoms and the variety in picture interpretation. This study utilizes modern machine learning can improve the accuracy and speed of diagnosing pneumonia using chest X-ray images. Utilizing a comprehensive dataset from the Kaggle online repository, consisting of over 5,000 annotated images, we evaluate the efficacy of various machine learning models including deep convolutional neural networks (CNN) and ensemble learning techniques. Our findings indicate that models like the Fuzzy opponent histogram filter combined with Logistic model trees (LMT) achieved the highest accuracy at 96.97%, while the deep learning-based Lenet (CNN) with LMT closely followed at 95.85%. The study aims to improve diagnostic precision, reduce interpretation discrepancies, and facilitate faster clinical decision-making by identifying the most effective machine learning approaches for real-world applications in healthcare settings. 2025 Kamal Upreti, Anju Singh, Divakar Singh, Preety Shoran, Uma Shankar, Meenakshi Yadav and Rituraj Jain.
Source
ARO-The Scientific Journal of Koya University;Volume;13;Issue;1;Article No.;12174;pp.215-226
Date
01-01-2025
Publisher
Koya University
Subject
Artificial intelligence; Chest X-rays; Fuzzy opponent histogram filter; Machine learning; Pneumonia
Coverage
Upreti K., Department of Computer Science, CHRIST (Deemed to be University), Delhi NCR Campus, Ghaziabad, India; Singh A., Department of Computer Science and Engineering, Lakshmi Narain College of Technology, Kalchuri Nagar, Raisen Road, Madhya Pradesh, Bhopal, India; Singh D., Department of Computer Science and Engineering, university Institute of Technology, Barkatullah University, Madhya Pradesh, Bhopal, India; Shoran P., Department of Computer Science, CHRIST (Deemed to be University), Delhi NCR Campus, Ghaziabad, India; Shankar U., Department of Management, Faculty of Management and Social Sciences, Qaiwan International University, Kurdistan, Sulaimanyah, Iraq; Yadav M., Department of Information Technology, Galgotias College of Engineering and Technology, Greater Noida, India; Jain R., Department of Information Technology, Marwadi University, Gujarat, Rajkot, India
Rights
All Open Access; Gold Open Access; Green Open Access
Relation
ISSN: 24109355;
Format
online
Language
English
Type
Article

Citation

Upreti, Kamal; Singh, Anju; Singh, Divakar; Shoran, Preety; Shankar, Uma; Yadav, Meenakshi; Jain, Rituraj, “Enhanced Pneumonia Detection from Chest X-rays Using Machine Learning and Deep Neural Architectures,” CHRIST (Deemed To Be University) Institutional Repository, accessed June 20, 2026, https://archives.christuniversity.in/items/show/23264.

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