European Spine Journal

Artificial intelligence, big data and precision spine care: a trend or the holy grail?

Dino Samartzis, Fabio Galbusera, Hans-Joachim Wilke

Can artificial intelligence support or even replace physicians in measuring sagittal balance? A validation study on preoperative and postoperative full spine images of 170 patients

Priyanka Grover, Jakob Siebenwirth, Christina Caspari, Steffen Drange, Marcel Dreischarf, Jean-Charles Le Huec, Michael Putzier, Jörg Franke

Machine learning-driven identification of novel patient factors for prediction of major complications after posterior cervical spinal fusion

Akash A. Shah, Sai K. Devana, Changhee Lee, Amador Bugarin, Elizabeth L. Lord, Arya N. Shamie, Don Y. Park, Mihaela van der Schaar, Nelson F. SooHoo

Learning-based fully automated prediction of lumbar disc degeneration progression with specified clinical parameters and preliminary validation

Jason Pui Yin Cheung, Xihe Kuang, Marcus Kin Long Lai, Kenneth Man-Chee Cheung, Jaro Karppinen, Dino Samartzis, Honghan Wu, Fengdong Zhao, Zhaomin Zheng, Teng Zhang

Comparison of manual versus automated measurement of Cobb angle in idiopathic scoliosis based on a deep learning keypoint detection technology

Yu Sun, Yaozhong Xing, Zian Zhao, Xianglong Meng, Gang Xu, Yong Hai

Use of machine learning to select texture features in investigating the effects of axial loading on T2-maps from magnetic resonance imaging of the lumbar discs

Vahid Abdollah, Eric C. Parent, Samin Dolatabadi, Erica Marr, Keith Wachowicz, Michele Battié

Identification of potentially painful disc fissures in magnetic resonance images using machine-learning modelling

Kerstin Lagerstrand, Hanna Hebelka, Helena Brisby

Use of machine learning to model surgical decision-making in lumbar spine surgery

Nathan Xie, Peter J. Wilson, Rajesh Reddy

Artificial intelligence and spine imaging: limitations, regulatory issues and future direction

Alexander L. Hornung, Christopher M. Hornung, G. Michael Mallow, J. Nicolas Barajas, Alejandro A. Espinoza Orías, Fabio Galbusera, Hans-Joachim Wilke, Matthew Colman, Frank M. Phillips, Howard S. An, Dino Samartzis

A deep learning-based method for the diagnosis of vertebral fractures on spine MRI: retrospective training and validation of ResNet

Lee-Ren Yeh, Yang Zhang, Jeon-Hor Chen, Yan-Lin Liu, An-Chi Wang, Jie-Yu Yang, Wei-Cheng Yeh, Chiu-Shih Cheng, Li-Kuang Chen, Min-Ying Su

Spinopelvic measurements of sagittal balance with deep learning: systematic review and critical evaluation

Tomaž Vrtovec, Bulat Ibragimov

Using hierarchical unsupervised learning to integrate and reduce multi-level and multi-paraspinal muscle MRI data in relation to low back pain

Abel Torres-Espin, Anastasia Keller, Gabriel T. A. Johnson, Aaron J. Fields, Roland Krug, Adam R. Ferguson, Alan R. Hargens, Conor W. O’Neill, Jeffrey C. Lotz, Jeannie F. Bailey

Artificial intelligence in spine care: current applications and future utility

Alexander L. Hornung, Christopher M. Hornung, G. Michael Mallow, J. Nicolás Barajas, Augustus Rush III, Arash J. Sayari, Fabio Galbusera, Hans-Joachim Wilke, Matthew Colman, Frank M. Phillips, Howard S. An, Dino Samartzis

Machine learning versus logistic regression for prognostic modelling in individuals with non-specific neck pain

Bernard X. W. Liew, Francisco M. Kovacs, David Rügamer, Ana Royuela

Automatic recognition of whole-spine sagittal alignment and curvature analysis through a deep learning technique

Chi-Hung Weng, Yu-Jui Huang, Chen-Ju Fu, Yu-Cheng Yeh, Chao-Yuan Yeh, Tsung-Ting Tsai

Artificial intelligence in predicting early-onset adjacent segment degeneration following anterior cervical discectomy and fusion

Samuel S. Rudisill, Alexander L. Hornung, J. Nicolás Barajas, Jack J. Bridge, G. Michael Mallow, Wylie Lopez, Arash J. Sayari, Philip K. Louie, Garrett K. Harada, Youping Tao, Hans-Joachim Wilke, Matthew W. Colman, Frank M. Phillips, Howard S. An, Dino Samartzis

A deep learning framework for vertebral morphometry and Cobb angle measurement with external validation

Danis Alukaev, Semen Kiselev, Tamerlan Mustafaev, Ahatov Ainur, Bulat Ibragimov, Tomaž Vrtovec

Development of a machine-learning based model for predicting multidimensional outcome after surgery for degenerative disorders of the spine

D. Müller, D. Haschtmann, T. F. Fekete, F. Kleinstück, R. Reitmeir, M. Loibl, D. O’Riordan, F. Porchet, D. Jeszenszky, A. F. Mannion

External validation of the deep learning system “SpineNet” for grading radiological features of degeneration on MRIs of the lumbar spine

Alexandra Grob, Markus Loibl, Amir Jamaludin, Sebastian Winklhofer, Jeremy C. T. Fairbank, Tamás Fekete, François Porchet, Anne F. Mannion

Performance of hybrid artificial intelligence in determining candidacy for lumbar stenosis surgery

Raphael Mourad, Serhii Kolisnyk, Yurii Baiun, Alessandra Falk, Titenkov Yuriy, Frolov Valerii, Aleksey Kopeev, Olga Suldina, Andrey Pospelov, Jack Kim, Andrej Rusakov, Darren R. Lebl

An externally validated deep learning model for the accurate segmentation of the lumbar paravertebral muscles

Frank Niemeyer, Annika Zanker, René Jonas, Youping Tao, Fabio Galbusera, Hans-Joachim Wilke

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