Machine Learning and Signal Processing Methodologies to Diagnose Human Knee Joint Disorders: A Computational Analysis · CHRIST (Deemed To Be University) Institutional Repository

Title: Machine Learning and Signal Processing Methodologies to Diagnose Human Knee Joint Disorders: A Computational Analysis
Description: Artificial Intelligence and Knowledge Processing: Improved Decision-Making and Prediction pp.119-130
Creator: Murugan R.; Balajee A.; Senbagamalar L.; Aadil M.; Ganie S.M.
Source: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85170182501&doi=10.1201%2f9781003328414-11&partnerID=40&md5=1b3de740e5aa2ba1d86c756a5f286978
Date: 2023-01-01

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Citation

Murugan R.; Balajee A.; Senbagamalar L.; Aadil M.; Ganie S.M., “Machine Learning and Signal Processing Methodologies to Diagnose Human Knee Joint Disorders: A Computational Analysis,” CHRIST (Deemed To Be University) Institutional Repository, accessed February 8, 2025, https://archives.christuniversity.in/items/show/8792.

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