The Science and Information (SAI) Organization
  • Home
  • About Us
  • Journals
  • Conferences
  • Contact Us

Publication Links

  • IJACSA
  • Author Guidelines
  • Publication Policies
  • Digital Archiving Policy
  • Promote your Publication
  • Metadata Harvesting (OAI2)

IJACSA

  • About the Journal
  • Call for Papers
  • Editorial Board
  • Author Guidelines
  • Submit your Paper
  • Current Issue
  • Archives
  • Indexing
  • Fees/ APC
  • Reviewers
  • Apply as a Reviewer

IJARAI

  • About the Journal
  • Archives
  • Indexing & Archiving

Special Issues

  • Home
  • Archives
  • Proposals
  • Guest Editors
  • SUSAI-EE 2025
  • ICONS-BA 2025
  • IoT-BLOCK 2025

Future of Information and Communication Conference (FICC)

  • Home
  • Call for Papers
  • Submit your Paper/Poster
  • Register
  • Venue
  • Contact

Computing Conference

  • Home
  • Call for Papers
  • Submit your Paper/Poster
  • Register
  • Venue
  • Contact

Intelligent Systems Conference (IntelliSys)

  • Home
  • Call for Papers
  • Submit your Paper/Poster
  • Register
  • Venue
  • Contact

Future Technologies Conference (FTC)

  • Home
  • Call for Papers
  • Submit your Paper/Poster
  • Register
  • Venue
  • Contact
  • Home
  • Call for Papers
  • Editorial Board
  • Guidelines
  • Submit
  • Current Issue
  • Archives
  • Indexing
  • Fees
  • Reviewers
  • Subscribe

DOI: 10.14569/IJACSA.2023.0140430
PDF

Fuzzy Rank-Based Ensemble Model for Accurate Diagnosis of Osteoporosis in Knee Radiographs

Author 1: Saumya Kumar
Author 2: Puneet Goswami
Author 3: Shivani Batra

International Journal of Advanced Computer Science and Applications(IJACSA), Volume 14 Issue 4, 2023.

  • Abstract and Keywords
  • How to Cite this Article
  • {} BibTeX Source

Abstract: The main factor in fractures among seniors and women post-menopausal is osteoporosis, which decreases the density of bones. Finding a low-cost diagnostic technology to identify osteoporosis in its initial stages is imperative considering the substantial expenses of diagnosis and therapy. The simplest and most widely used imaging method for detecting bone diseases is X-ray radiography, however, it is problematic to manually examine X-rays for osteoporosis as well as to identify the essential components and choose elevated classifiers. To categorize x-ray pictures of knee joints into normal, osteopenia, and osteoporosis condition categories, authors present a process in this investigation that uses three convolutional neural networks (CNN) architectures, i.e., Inception v3, Xception, and ResNet 18, to create an ensemble-based classifier model. The suggested ensemble approach employs a fuzzy rank-based unification of classifiers by taking into account two distinct parameters on the decision scores produced by the aforementioned base classifiers. Contrary to the straightforward fusion strategies that have been mentioned in the literature, the suggested ensemble methodology finalizes predictions on the test specimens by considering the confidence in the recommendations of the base learners. A 5-fold cross-validation approach has been employed to assess the developed framework using a benchmark dataset that has been made accessible to the general population. The suggested model yields an accuracy rate of 93.5% with a loss of 0.082. Further, the AUC is observed to be 98.1, 97.9 and 97.3 for normal, osteopenia and osteoporosis, respectively. The results demonstrate the model’s usefulness by outperforming various state-of-the-art approaches.

Keywords: Convolutional Neural Network; diagnosis; knee; osteoporosis; transfer learning models; X-rays

Saumya Kumar, Puneet Goswami and Shivani Batra, “Fuzzy Rank-Based Ensemble Model for Accurate Diagnosis of Osteoporosis in Knee Radiographs” International Journal of Advanced Computer Science and Applications(IJACSA), 14(4), 2023. http://dx.doi.org/10.14569/IJACSA.2023.0140430

@article{Kumar2023,
title = {Fuzzy Rank-Based Ensemble Model for Accurate Diagnosis of Osteoporosis in Knee Radiographs},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2023.0140430},
url = {http://dx.doi.org/10.14569/IJACSA.2023.0140430},
year = {2023},
publisher = {The Science and Information Organization},
volume = {14},
number = {4},
author = {Saumya Kumar and Puneet Goswami and Shivani Batra}
}



Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

IJACSA

Upcoming Conferences

IntelliSys 2025

28-29 August 2025

  • Amsterdam, The Netherlands

Future Technologies Conference 2025

6-7 November 2025

  • Munich, Germany

Healthcare Conference 2026

21-22 May 2026

  • Amsterdam, The Netherlands

Computing Conference 2026

9-10 July 2026

  • London, United Kingdom

IntelliSys 2026

3-4 September 2026

  • Amsterdam, The Netherlands

Computer Vision Conference 2026

15-16 October 2026

  • Berlin, Germany
The Science and Information (SAI) Organization
BACK TO TOP

Computer Science Journal

  • About the Journal
  • Call for Papers
  • Submit Paper
  • Indexing

Our Conferences

  • Computing Conference
  • Intelligent Systems Conference
  • Future Technologies Conference
  • Communication Conference

Help & Support

  • Contact Us
  • About Us
  • Terms and Conditions
  • Privacy Policy

© The Science and Information (SAI) Organization Limited. All rights reserved. Registered in England and Wales. Company Number 8933205. thesai.org