TY - JOUR
T1 - Artificial intelligence and computer vision in orthopaedic trauma
T2 - the why, what, and how
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 M. M. J.
AU - Laane, Charlotte
AU - Nijhuis, Koen Oude
AU - van Ooijen, Peter
AU - Oosterhoff, Jacobien H.F.
AU - Ring, David
AU - Schwab, Joseph H.
AU - Sprague, Sheila
AU - Stirler, Vincent
AU - Wijffels, Matthieu
PY - 2022/8
Y1 - 2022/8
N2 - 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').
AB - 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').
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 - http://www.scopus.com/inward/record.url?scp=85135208004&partnerID=8YFLogxK
U2 - 10.1302/0301-620X.104B8.BJJ-2022-0119.R1
DO - 10.1302/0301-620X.104B8.BJJ-2022-0119.R1
M3 - Article
C2 - 35909378
AN - SCOPUS:85135208004
SN - 2049-4408
VL - 104-B
SP - 911
EP - 914
JO - The bone & joint journal
JF - The bone & joint journal
IS - 8
ER -