About the Journal

Indian Journal of Engineering Research Networking and Development aims to provide a comprehensive platform for researchers, academics, and professionals to publish, discover, and access high-quality scholarly journals across Computer Science disciplines. Our mission is to facilitate the dissemination of knowledge and foster collaboration within the academic community.
 
Key Features:
 
1. User-friendly Publication Platform:  Indian Journal of Engineering Research Networking and Development offers a user-friendly interface for authors to submit their research papers, articles, and manuscripts. The submission process is streamlined, allowing authors to easily upload their work and track the status of their submissions.
 
2. Peer Review System: All submissions undergo a rigorous peer review process to ensure the quality and credibility of published content. Our platform enables efficient peer review management, with tools for reviewers to assess submissions and provide constructive feedback to authors.
 
3. Open Access Publishing: We support open access publishing, making research freely accessible to readers worldwide. Authors have the option to publish their work under open access licenses, promoting greater visibility and impact for their research.
 
4. Advanced Search and Discovery: Users can easily discover relevant research articles using our advanced search and filtering options. The website provides tools to explore journals, browse articles by category, keyword, or author, and stay updated with the latest publications in their areas of interest.
 
5. Community Engagement:  Indian Journal of Engineering Research Networking and Development fosters a vibrant academic community by facilitating discussions, collaborations, and networking among researchers, scholars, and practitioners. Users can engage with content through comments, ratings, and sharing features.
 
6. Responsive Design: Our website is optimized for seamless browsing across desktop, tablet, and mobile devices, ensuring accessibility and usability for users on the go.
 
7. Editorial Board: Each journal on  Indian Journal of Engineering Research Networking and Development is managed by an esteemed editorial board comprising experts in the respective field. The editorial board ensures the integrity and scholarly rigor of published content.
 
8. Analytics and Metrics: Authors and journal editors have access to comprehensive analytics and metrics to track the performance and impact of their publications. Metrics include citation counts, download statistics.
 
Future Developments:
 
1. Integration with ORCID: Implement integration with ORCID (Open Researcher and Contributor ID) to streamline author identification and authentication processes.
 
2. Enhanced Collaboration Tools: Develop features for collaborative research projects, such as shared document editing, project management, and communication tools for research teams.
 
3. AI-powered Recommendation System: Implement an AI-powered recommendation system to suggest relevant articles, journals, and researchers based on user preferences and browsing history.
 
4. Expanded Content Types: Introduce support for additional content types such as preprints, datasets, multimedia content, and supplementary materials to enhance the diversity of published research.
 
5. Global Outreach Initiatives: Launch initiatives to promote inclusivity and diversity in scholarly publishing, including translation services, mentorship programs, and partnerships with institutions in underrepresented regions.
 
 Indian Journal of Engineering Research Networking and Development is committed to advancing the dissemination of knowledge and empowering researchers worldwide through our innovative platform.
 
Year of Starting:-2024
 
Format of Publication : Online
 
Subject:-The Indian Journal of Engineering Research Networking and Development  is a premier peer-reviewed journal dedicated to advancing research and knowledge in the fields of computer Science .Our mission is to provide a platform for researchers, practitioners, and academics to publish high-quality, innovative, and impactful research that contributes to the development .
 
 
 
 

Current Issue

Vol. 2 No. 04 (2025): Deep Learning-Powered Automated Detection of Abnormalities in Chest X-Rays
					View Vol. 2 No. 04 (2025): Deep Learning-Powered Automated Detection of Abnormalities in Chest X-Rays

Abstract

Medical imaging plays a crucial role in diagnosing various diseases and abnormalities within the human body, with chest X-rays being one of the most commonly used modalities. In recent years, deep learning techniques have shown remarkable promise in automating the analysis of medical images, including the detection of abnormalities in chest X-rays. This project aims to explore the application of deep learning algorithms, particularly convolutional neural networks (CNNs), for the automated detection of abnormal findings in chest X-rays. The project will involve the collection and preprocessing of a diverse dataset of chest X-ray images, encompassing both normal and abnormal cases. Subsequently, deep learning models will be trained, validated, and fine-tuned using the collected dataset to accurately classify chest X-rays as either normal or abnormal based on the presence of various pathologies such as pneumonia, lung nodules, or pleural effusion. The performance of the developed models will be evaluated using standard metrics such as accuracy, sensitivity, specificity, and area under the receiver operating characteristic curve (AUC-ROC). The outcomes of this project aim to contribute to the advancement of computer-aided diagnosis systems in healthcare, potentially aiding clinicians in making more accurate and timely diagnoses, thus improving patient outcomes.

Index Terms

Medical Imaging, Chest X-rays, Deep Learning, Convolutional Neural Networks (CNNs), Automated Detection, Abnormal Findings, Dataset Collection, Preprocessing, Pathologies, Pneumonia, Lung Nodules, Pleural Effusion, Performance Evaluation, Accuracy, Sensitivity, Specificity, Area Under the Receiver Operating Characteristic Curve (AUC-ROC), Computer-Aided Diagnosis Systems, Healthcare, Patient Outcomes.

 

 

Published: 2025-04-26

Articles

  • Deep Learning-Powered Automated Detection of Abnormalities in Chest X-Rays

    DOI: https://doi.org/10.1234/e0fk3n85
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