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The Bone & Joint Journal
Vol. 103-B, Issue 9 | Pages 1442 - 1448
1 Sep 2021
McDonnell JM Evans SR McCarthy L Temperley H Waters C Ahern D Cunniffe G Morris S Synnott K Birch N Butler JS

In recent years, machine learning (ML) and artificial neural networks (ANNs), a particular subset of ML, have been adopted by various areas of healthcare. A number of diagnostic and prognostic algorithms have been designed and implemented across a range of orthopaedic sub-specialties to date, with many positive results. However, the methodology of many of these studies is flawed, and few compare the use of ML with the current approach in clinical practice. Spinal surgery has advanced rapidly over the past three decades, particularly in the areas of implant technology, advanced surgical techniques, biologics, and enhanced recovery protocols. It is therefore regarded an innovative field. Inevitably, spinal surgeons will wish to incorporate ML into their practice should models prove effective in diagnostic or prognostic terms. The purpose of this article is to review published studies that describe the application of neural networks to spinal surgery and which actively compare ANN models to contemporary clinical standards allowing evaluation of their efficacy, accuracy, and relatability. It also explores some of the limitations of the technology, which act to constrain the widespread adoption of neural networks for diagnostic and prognostic use in spinal care. Finally, it describes the necessary considerations should institutions wish to incorporate ANNs into their practices. In doing so, the aim of this review is to provide a practical approach for spinal surgeons to understand the relevant aspects of neural networks.

Cite this article: Bone Joint J 2021;103-B(9):1442–1448.


The Journal of Bone & Joint Surgery British Volume
Vol. 81-B, Issue 6 | Pages 979 - 981
1 Nov 1999
Kenny P O’Brien CP Synnott K Walsh MG

We have carried out a blind, prospective study of 50 consecutive patients undergoing replacement arthroplasty of the hip using two different approaches. Clinical assessment, including the Harris hip score and a modified Trendelenberg test, and electrophysiological examination of the abductor muscles of the hip were undertaken before and three months after surgery. We found that 48% of patients had preoperative evidence of chronic injury to the superior gluteal nerve. Perioperative injury to the nerve occurred commonly with both approaches to the hip.

We did not find a significant correlation between injury to the superior gluteal nerve and clinical problems.