Pullout Strength Predictor: A Machine Learning Approach-Reference-Cited by-同舟云学术

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Pullout Strength Predictor: A Machine Learning Approach

Published:2019-10-31 Issue:5 Volume:13 Page:842-848
ISSN:1976-1902
Container-title:Asian Spine Journal
language:en
Short-container-title:Asian Spine J

Author:

Khatri Ravi,Varghese Vicky,Sharma Sunil,Kumar Gurunathan Saravana,Chhabra Harvinder Singh

Publisher

Asian Spine Journal (ASJ)

Subject

Orthopedics and Sports Medicine,Surgery

Link

http://www.asianspinejournal.org/upload/pdf/asj-2018-0243.pdf

Reference30 articles.

1. The Epidemiology of low back pain

2. Instrumentation of the osteoporotic spine: biomechanical and clinical considerations

3. Pull out strength of pedicle screw in normal and osteoporotic cancellous bone models

4. A finite element analysis based sensitivity studies on pull out strength of pedicle screw in synthetic osteoporotic bone models

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1. The Evolution of Risk Assessment in Spine Surgery: A Narrative Review;World Neurosurgery;2024-08

2. Design, fabrication, and evaluation of single- and multi-level 3D-printed non-covering cervical spinal fusion surgery templates;Frontiers in Bioengineering and Biotechnology;2024-07-12

3. Exoscope-assisted spine surgery: Current applications and future directions;World Neurosurgery: X;2024-07

4. Artificial intelligence: a new cutting-edge tool in spine surgery;Asian Spine Journal;2024-06-30

5. Biomechanical Study of 3 Osteoconductive Materials Applied in Pedicle Augmentation and Revision for Osteoporotic Vertebrae: Allograft Bone Particles, Calcium Phosphate Cement, Demineralized Bone Matrix;Neurospine;2023-12-31

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