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

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.104B8.BJJ-2022-0119.R1

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

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 › Article › peer-review

4 Citations (Scopus)

Abstract

Artificial intelligence (AI) is, in essence, the concept of 'computer thinking', encompassing methods that train computers to perform and learn from executing certain tasks, called machine learning, and methods to build intricate computer models that both learn and adapt, called complex neural networks. Computer vision is a function of AI by which machine learning and complex neural networks can be applied to enable computers to capture, analyze, and interpret information from clinical images and visual inputs. This annotation summarizes key considerations and future perspectives concerning computer vision, questioning the need for this technology (the 'why'), the current applications (the 'what'), and the approach to unlocking its full potential (the 'how').

Original language	English
Pages (from-to)	911-914
Number of pages	4
Journal	The bone & joint journal
Volume	104-B
Issue number	8
DOIs	https://doi.org/10.1302/0301-620X.104B8.BJJ-2022-0119.R1
Publication status	Published - Aug 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

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10.1302/0301-620X.104B8.BJJ-2022-0119.R1Licence: In Copyright

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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). Artificial intelligence and computer vision in orthopaedic trauma: the why, what, and how. The bone & joint journal, 104-B(8), 911-914. https://doi.org/10.1302/0301-620X.104B8.BJJ-2022-0119.R1

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abstract = "Artificial intelligence (AI) is, in essence, the concept of 'computer thinking', encompassing methods that train computers to perform and learn from executing certain tasks, called machine learning, and methods to build intricate computer models that both learn and adapt, called complex neural networks. Computer vision is a function of AI by which machine learning and complex neural networks can be applied to enable computers to capture, analyze, and interpret information from clinical images and visual inputs. This annotation summarizes key considerations and future perspectives concerning computer vision, questioning the need for this technology (the 'why'), the current applications (the 'what'), and the approach to unlocking its full potential (the 'how'). ",

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

Abstract

Keywords

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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)

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