Corrigendum: Artificial intelligence and computer vision in orthopaedic trauma: the why, how, and what (Bone Joint J. (2022) 104-B: 8 (911–914) DOI: 10.1302/0301-620X.104B8.BJJ-2022-0119.R1)

Jasper Prijs; Zhibin Liao; Soheil Ashkani-Esfahani; Jakub Olczak; Max Gordon; Prakash Jayakumar; Paul C. Jutte; Ruurd L. Jaarsma; Frank F.A. IJpma; Job N. Doornberg; Machine Learning Consortium

doi:10.1302/0301-620X.104B9.BJJ-2022-00026

Corrigendum: Artificial intelligence and computer vision in orthopaedic trauma: the why, how, and what (Bone Joint J. (2022) 104-B: 8 (911–914) DOI: 10.1302/0301-620X.104B8.BJJ-2022-0119.R1)

Jasper Prijs
, Zhibin Liao
, Soheil Ashkani-Esfahani
, Jakub Olczak
, Max Gordon
, Prakash Jayakumar
, Paul C. Jutte
, Ruurd L. Jaarsma
, Frank F.A. IJpma
, Job N. Doornberg
, Machine Learning Consortium

College of Medicine and Public Health

Research output: Contribution to journal › Comment/debate

Abstract

Artificial intelligence and computer vision in orthopaedic trauma: the why, how, and what Published online 1 August 2020 https://online.boneandjoint.org.uk/doi/full/10.1302/0301-620X.104B8.BJJ-2022-0119.R1 and in Bone Joint J. 2022;104-B(8):911–914. The term “convolutional neural network” was mistakenly given as “complex neural network” and repeated throughout.

Original language	English
Pages (from-to)	1189
Number of pages	1
Journal	Bone and Joint Journal
Volume	104-B
Issue number	10
DOIs	https://doi.org/10.1302/0301-620X.104B9.BJJ-2022-00026
Publication status	Published - 1 Oct 2022

Keywords

AI
artificial Intelligence
clinicians
CNN
CT scans
detection
haemorrhage
machine learning
medical images
orthopaedic images
orthopaedic surgery
orthopaedic trauma
postoperative infection
radiographs
trauma surgery

Access to Document

10.1302/0301-620X.104B9.BJJ-2022-00026Licence: In Copyright

Cite this

Prijs, J., Liao, Z., Ashkani-Esfahani, S., Olczak, J., Gordon, M., Jayakumar, P., Jutte, P. C., Jaarsma, R. L., IJpma, F. F. A., Doornberg, J. N., & Machine Learning Consortium (2022). Corrigendum: Artificial intelligence and computer vision in orthopaedic trauma: the why, how, and what (Bone Joint J. (2022) 104-B: 8 (911–914) DOI: 10.1302/0301-620X.104B8.BJJ-2022-0119.R1). Bone and Joint Journal, 104-B(10), 1189. https://doi.org/10.1302/0301-620X.104B9.BJJ-2022-00026

@article{5e1eb8ff52cf4886bacbb14913b4c901,

title = "Corrigendum: Artificial intelligence and computer vision in orthopaedic trauma: the why, how, and what (Bone Joint J. (2022) 104-B: 8 (911–914) DOI: 10.1302/0301-620X.104B8.BJJ-2022-0119.R1)",

abstract = "Artificial intelligence and computer vision in orthopaedic trauma: the why, how, and what Published online 1 August 2020 https://online.boneandjoint.org.uk/doi/full/10.1302/0301-620X.104B8.BJJ-2022-0119.R1 and in Bone Joint J. 2022;104-B(8):911–914. The term “convolutional neural network” was mistakenly given as “complex neural network” and repeated throughout.",

keywords = "AI, artificial Intelligence, clinicians, CNN, CT scans, detection, haemorrhage, machine learning, medical images, orthopaedic images, orthopaedic surgery, orthopaedic trauma, postoperative infection, radiographs, trauma surgery",

author = "Jasper Prijs and Zhibin Liao and Soheil Ashkani-Esfahani and Jakub Olczak and Max Gordon and Prakash Jayakumar and Jutte, \{Paul C.\} and Jaarsma, \{Ruurd L.\} and IJpma, \{Frank F.A.\} and Doornberg, \{Job N.\} and \{Machine Learning Consortium\} and Britt Barvelink and Joost Colaris and Chris DiGiovanni and Andrew Duckworth and Hamid Ghaednia and Daniel Guss and Merilyn Heng and Sanne Hoeksema and Mike Hogervorst and Gino Kerkhoffs and Charlotte Laane and Nijhuis, \{Koen Oude\} and \{van Ooijen\}, Peter and Jacobien Oosterhoff and David Ring and Joseph Schwab and Sheila Sprague and Vincent Stirler and Matthieu Wijffels",

year = "2022",

month = oct,

day = "1",

doi = "10.1302/0301-620X.104B9.BJJ-2022-00026",

language = "English",

volume = "104-B",

pages = "1189",

journal = "Bone and Joint Journal",

issn = "2049-4394",

publisher = "British Editorial Society of Bone and Joint Surgery",

number = "10",

}

Prijs, J, Liao, Z, Ashkani-Esfahani, S, Olczak, J, Gordon, M, Jayakumar, P, Jutte, PC, Jaarsma, RL, IJpma, FFA, Doornberg, JN & Machine Learning Consortium 2022, 'Corrigendum: Artificial intelligence and computer vision in orthopaedic trauma: the why, how, and what (Bone Joint J. (2022) 104-B: 8 (911–914) DOI: 10.1302/0301-620X.104B8.BJJ-2022-0119.R1)', Bone and Joint Journal, vol. 104-B, no. 10, pp. 1189. https://doi.org/10.1302/0301-620X.104B9.BJJ-2022-00026

Corrigendum: Artificial intelligence and computer vision in orthopaedic trauma: the why, how, and what (Bone Joint J. (2022) 104-B: 8 (911–914) DOI: 10.1302/0301-620X.104B8.BJJ-2022-0119.R1). / Prijs, Jasper; Liao, Zhibin; Ashkani-Esfahani, Soheil et al.
In: Bone and Joint Journal, Vol. 104-B, No. 10, 01.10.2022, p. 1189.

Research output: Contribution to journal › Comment/debate

TY - JOUR

T1 - Corrigendum

T2 - Artificial intelligence and computer vision in orthopaedic trauma: the why, how, and what (Bone Joint J. (2022) 104-B: 8 (911–914) DOI: 10.1302/0301-620X.104B8.BJJ-2022-0119.R1)

AU - Prijs, Jasper

AU - Liao, Zhibin

AU - Ashkani-Esfahani, Soheil

AU - Olczak, Jakub

AU - Gordon, Max

AU - Jayakumar, Prakash

AU - Jutte, Paul C.

AU - Jaarsma, Ruurd L.

AU - IJpma, Frank F.A.

AU - Doornberg, Job N.

AU - Machine Learning Consortium

AU - Barvelink, Britt

AU - Colaris, Joost

AU - DiGiovanni, Chris

AU - Duckworth, Andrew

AU - Ghaednia, Hamid

AU - Guss, Daniel

AU - Heng, Merilyn

AU - Hoeksema, Sanne

AU - Hogervorst, Mike

AU - Kerkhoffs, Gino

AU - Laane, Charlotte

AU - Nijhuis, Koen Oude

AU - van Ooijen, Peter

AU - Oosterhoff, Jacobien

AU - Ring, David

AU - Schwab, Joseph

AU - Sprague, Sheila

AU - Stirler, Vincent

AU - Wijffels, Matthieu

PY - 2022/10/1

Y1 - 2022/10/1

N2 - Artificial intelligence and computer vision in orthopaedic trauma: the why, how, and what Published online 1 August 2020 https://online.boneandjoint.org.uk/doi/full/10.1302/0301-620X.104B8.BJJ-2022-0119.R1 and in Bone Joint J. 2022;104-B(8):911–914. The term “convolutional neural network” was mistakenly given as “complex neural network” and repeated throughout.

AB - Artificial intelligence and computer vision in orthopaedic trauma: the why, how, and what Published online 1 August 2020 https://online.boneandjoint.org.uk/doi/full/10.1302/0301-620X.104B8.BJJ-2022-0119.R1 and in Bone Joint J. 2022;104-B(8):911–914. The term “convolutional neural network” was mistakenly given as “complex neural network” and repeated throughout.

KW - AI

KW - artificial Intelligence

KW - clinicians

KW - CNN

KW - CT scans

KW - detection

KW - haemorrhage

KW - machine learning

KW - medical images

KW - orthopaedic images

KW - orthopaedic surgery

KW - orthopaedic trauma

KW - postoperative infection

KW - radiographs

KW - trauma surgery

UR - https://www.scopus.com/pages/publications/85138905946

U2 - 10.1302/0301-620X.104B9.BJJ-2022-00026

DO - 10.1302/0301-620X.104B9.BJJ-2022-00026

M3 - Comment/debate

C2 - 36177648

AN - SCOPUS:85138905946

SN - 2049-4394

VL - 104-B

SP - 1189

JO - Bone and Joint Journal

JF - Bone and Joint Journal

IS - 10

ER -

Corrigendum: Artificial intelligence and computer vision in orthopaedic trauma: the why, how, and what (Bone Joint J. (2022) 104-B: 8 (911–914) DOI: 10.1302/0301-620X.104B8.BJJ-2022-0119.R1)

Abstract

Keywords

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Artificial intelligence and computer vision in orthopaedic trauma: the why, what, and how

Cite this