Paper Title
Detection of Pneumonia using Fuzzy Expert System
Article Identifiers
Authors
Rakshitha B , Sanjana P Rao , Sanjana T M , Shilpashree B C , Dr. Manu A P
Keywords
Pneumonia, fuzzy expert system, CNN, VGG16, ResNet50V2, X-Ray image.
Abstract
Respiratory diseases, especially pneumonia, are a global health problem that still requires accurate and effective diagnosis. The system uses an expert fuzzy system to integrate key measurements such as body temperature, sputum, sputum color, chest pain, dyspnea(shortness of breath), respiratory rate, heart rate, systolic blood pressure and white blood count. These parameters form the basis of a good decision-making model and reflect the complexity of pneumonia diagnosis. Moreover, to improve diagnostic accuracy, our system includes a chest X-ray image processed by convolutional neural networks (CNN), including models such as VGG16 and ResNet50V2. This bimodal approach is designed to use both quantitative clinical data and qualitative data, allowing efficient and accurate assessment of pneumonia pressence. Fuzzy expert systems use fuzzy logic to model uncertainty in diagnosis and provide a flexible model for fuzzy thinking. The integration of image processing technology not only makes it easier to extract X-ray images from X-ray, but also creates hybrid decisions. This combination gives the percentage chance of getting pneumonia to help doctors make decisions. The proposed model was validated using different datasets. Performance measurements including sensitivity, specificity, and accuracy demonstrate the effectiveness of our method compared to traditional methods. The integration of clinical and image-based features makes the system reliable and useful in early and accurate diagnosis of pneumonia diagnosis. This study bridges the gap between traditional clinical examination and new technology, laying the foundation for a more nuanced and sophisticated way to diagnose pneumonia diagnosis.
Downloads
How To Cite (APA)
Rakshitha B, Sanjana P Rao, Sanjana T M, Shilpashree B C, & Dr. Manu A P (April-2024). Detection of Pneumonia using Fuzzy Expert System. INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT, 9(4), h717-h721. https://ijnrd.org/papers/IJNRD2404776.pdf
Issue
Volume 9 Issue 4, April-2024
Pages : h717-h721
Other Publication Details
Paper Reg. ID: IJNRD_212500
Published Paper Id: IJNRD2404776
Downloads: 000121961
Research Area: Engineering
Country: Shivamogga, Karnataka, India
Published Paper PDF: https://ijnrd.org/papers/IJNRD2404776.pdf
Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2404776
About Publisher
Journal Name: INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT(IJNRD)
ISSN: 2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar | ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.76 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator
Publisher: IJNRD (IJ Publication) Janvi Wave | IJNRD.ORG | IJNRD.COM | IJPUB.ORG
Licence
This work is licensed under a Creative Commons Attribution 4.0 International License and The Open Definition
Publication Timeline
Article Preview: View Full Paper
Call For Paper
IJNRD is a Scholarly Open Access, Peer-reviewed, and Refereed Journal with a High Impact Factor of 8.76 (calculated by Google Scholar & Semantic Scholar | AI-Powered Research Tool). It is a Multidisciplinary, Monthly, Low-Cost Journal that follows UGC CARE 2025 Peer-Reviewed Journal Policy norms, Scopus journal standards, and Transparent Peer Review practices to ensure quality and credibility. IJNRD provides indexing in all major databases & metadata repositories, a citation generator, and Digital Object Identifier (DOI) for every published article with full open-access visibility.
The INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT (IJNRD) aims to advance applied, theoretical, and experimental research across diverse fields. Its goal is to promote global scientific information exchange among researchers, developers, engineers, academicians, and practitioners. IJNRD serves as a platform where educators and professionals can share research evidence, models of best practice, and innovative ideas, contributing to academic growth and industry relevance.
Indexing Coverage includes Google Scholar, SSRN, ResearcherID-Publons, Semantic Scholar (AI-Powered Research Tool), Microsoft Academic, Academia.edu, arXiv.org, ResearchGate, CiteSeerX, ResearcherID (Thomson Reuters), Mendeley, DocStoc, ISSUU, Scribd, and many more recognized academic repositories.
How to submit the paper?
By Our website
Click Here to Submit Paper Online
Important Dates for Current issue
Paper Submission Open For: September 2025
Current Issue: Volume 10 | Issue 9 | September 2025
Impact Factor: 8.76
Last Date for Paper Submission: Till 30-Sep-2025
Notification of Review Result: Within 1-2 Days after Submitting paper.
Publication of Paper: Within 01-02 Days after Submititng documents.
Frequency: Monthly (12 issue Annually).
Journal Type: IJNRD is an International Peer-reviewed, Refereed, and Open Access Journal with Transparent Peer Review as per the new UGC CARE 2025 guidelines, offering low-cost multidisciplinary publication with Crossref DOI and global indexing.
Subject Category: Research Area
Call for Paper: More Details
