Machine Learning Techniques for the Diagnosis of Disc Disorders: Comparative Analysis
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Publisher
Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-27524-1_47
Reference20 articles.
1. Teraguchi, M., Yoshimura, N., et al.: Prevalence and distribution of intervertebral disc degeneration over the entire spine in a population-based cohort: the Wakayama Spine Study. Osteoarthritis and Cartilage 22(1), 104-110 (January 2014)
2. Jouko, S., Erkintalo Minna, O., et al.: Recurrent Low Back Pain and Early Disc Degeneration in the Young. Spine 24(13), 1316 (July 1 1999)
3. Steenstra, I.A., Verbeek, J.H., Heymans, M.W., Bongers, P.M.: Prognostic factors for duration of sick leave in patients sick listed with acute low back pain: a systematic review of the literature. Occup Environ Med. 62(12), 851–60 (2005)
4. Ravindra, V.M., Senglaub, S.S., Rattani, A., et al.: Degenerative lumbar spine disease: estimating global incidence and worldwide volume. Global Spine J. 8(8), 784–794 (2018). https://doi.org/10.1177/2192568218770769
5. Taher, F., et al.: Lumbar degenerative disc disease: current and future concepts of diagnosis and management. Hindawi Publishing Corporation Advances in Orthopaedics, vol. 2012, Article ID 970752, p. 7. https://doi.org/10.1155/2012/970752
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