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  Published Paper Details:

  Paper Title

Review on Osteoarthritis Detection: Leveraging Machine Learning and Deep Learning Algorithms

  Authors

  Komal Deokar,  Dr. Brijendra Gupta

  Keywords

Artificial Intelligence, Osteoarthritis, Knee X-Ray, machine learning, Deep learning.

  Abstract


Connective tissue that helps the joints and bones is named as Cartilage is present between the bones; Osteoarthritis (OA) means degradation of the tissues present in between the bones. It affects the lots of population worldwide which leads to ache, Rigidity, and Immobility. Detecting the Osteoarthritis in early stages and classification are difficult for accurate analysis and proper treatment. Treatments which are followed earlier are totally depends upon the clinical investigations like radiographic x-ray images, this type of treatment is very time-consuming. Latest research of machine learning and deep learning under Artificial Intelligence techniques of provides much better solution for the medical imaging findings, gives belter solution for analysis detection and classification of osteoarthritis (OA) using different types of imaging technologies. This review combines recent research on Osteoarthritis detection and classification techniques used in machine learning and deep learning approaches. This review papers explores the models from machine and deep learning, dimensionality reduction technologies, hybrid models, and future research directions.

  IJCRT's Publication Details

  Unique Identification Number - IJCRT2410663

  Paper ID - 271337

  Page Number(s) - f676-f682

  Pubished in - Volume 12 | Issue 10 | October 2024

  DOI (Digital Object Identifier) -    http://doi.one/10.1729/Journal.44752

  Publisher Name - IJCRT | www.ijcrt.org | ISSN : 2320-2882

  E-ISSN Number - 2320-2882

  Cite this article

  Komal Deokar,  Dr. Brijendra Gupta,   "Review on Osteoarthritis Detection: Leveraging Machine Learning and Deep Learning Algorithms", International Journal of Creative Research Thoughts (IJCRT), ISSN:2320-2882, Volume.12, Issue 10, pp.f676-f682, October 2024, Available at :http://www.ijcrt.org/papers/IJCRT2410663.pdf

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ISSN: 2320-2882
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Journal Starting Year (ESTD) : 2013
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ISSN and 7.97 Impact Factor Details


ISSN
ISSN
ISSN: 2320-2882
Impact Factor: 7.97 and ISSN APPROVED
Journal Starting Year (ESTD) : 2013
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