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Branch - Computer Application
Faculty - Faculty of Computer Application
Date of Registration - 8th February 2019
Supervisor - Dr. Shweta Agrawal.
Date of Ph.D. Viva - 26th August 2022
Title - Investigation of Deep Learning Model for Prediction of Lumar Spondylolisthesis through X-Ray Images
1. D. Saravagi and S. Agrawal, “Classification of Spondylolisthesis using DBSCAN attribute weighting algorithm”, Wesleyan Journal of Research, Vol.14 No1(XXXI). (UGC Care).
2. D. Saravagi, S. Agrawal and M. Saravagi, "Opportunities and challenges of machine learning models for prediction and diagnosis of spondylolisthesis: a systematic review", International Journal of Engineering Systems Modelling and Simulation, vol. 12, no. 2/3, p. 1, 2021. Available: 10.1504/ijesms.2021.10036751. (UGC Care & Scopus indexed Journal).
3. D. Saravagi, S. Agrawal, M. Saravagi, J. Chatterjee and M. Agarwal, "Diagnosis of Lumbar Spondylolisthesis Using Optimized Pretrained CNN Models", Computational Intelligence and Neuroscience, vol. 2022, pp. 1-12, 2022. Available: 10.1155/2022/7459260. (SCI Indexed).
4. D. Saravagi, S. Agrawal, M. Saravagi and M. Rahman, "Diagnosis of Lumbar spondylolisthesis Using a Pruned CNN Model", Computational and Mathematical Methods in Medicine, vol. 2022, pp. 1-10, 2022. Available: 10.1155/2022/2722315. (SCI Indexed).
5. Research paper on “Lumbar spondylolisthesis Diagnosis on Gradio using GGCapsNet” is Communicated to Journal of Healthcare Engineering.