Intelligent Medical Diagnostic System for Osteoarthritis using Deep Learning

Ayesha Asif Sayyad and Rajesh Keshavrao Deshmukh

International Journal of Scientific Research in Science and Technology, 2025, vol. 12, issue 2, 53-64

Abstract: Osteoarthritis (OA) is a prevalent joint disorder, particularly impacting older and overweight individuals, leading to diminished quality of life and increased frailty. This review paper focuses on the current diagnostic methods for OA, which primarily rely on clinical examinations and imaging techniques. However, these approaches may lack efficiency and precision, prompting the need for advanced diagnostic systems. This paper proposes an Intelligent Medical Diagnostic System for Osteoarthritis utilizing deep learning and medical imaging. By integrating deep features with medical images, the system aims to accurately detect and classify OA, particularly in the knee joint. Challenges such as irrelevant feature selection and managing large image datasets are addressed, alongside an exploration of Magnetic Resonance Imaging (MRI) techniques for OA detection and classification. The review provides a comprehensive discussion on location strategies, feature extraction techniques, and classification methods pertinent to OA diagnosis, highlighting recent advancements and future research directions.

Keywords: Osteoarthritis; deep learning; medical imaging; MRI; diagnostic system; joint health; frailty; cartilage deterioration; feature extraction; classification methods; research directions (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
https://ijsrst.com/home/article/view/IJSRST25121214 Abstract page (text/html)
https://ijsrst.com/home/article/download/IJSRST25121214/IJSRST25121214 Full text (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:etm:ijsrst:v12:y2025:i2:id:630

DOI: 10.32628/IJSRST25121214

Access Statistics for this article

More articles in International Journal of Scientific Research in Science and Technology from Technoscience Academy
Bibliographic data for series maintained by Pankaj Sharma ().