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E Carlos Rodríguez-Merchán

Introduction Artificial intelligence (AI) is an iterative process by which a machine captures information, transforms it into knowledge, and produces reactions that modify the environment. AI is a broad concept, involving virtual (computing

Jacobien H.F. Oosterhoff, Job N. Doornberg, and Machine Learning Consortium

Introduction Artificial intelligence (AI) is believed to have the capacity to change the scope of medicine, much as the introduction of smartphones changed our day-to-day lives. AI and machine learning (ML) are terms commonly used to cover a

Agnieszka Halm-Pozniak, Christoph H Lohmann, Luigi Zagra, Benedikt Braun, Max Gordon, and Bernd Grimm

innovative based on one main technology but usually combine several technologies such as for instance a virtual (digital) twin for preoperative planning where imaging techniques enhanced by artificial intelligence (AI) and virtual reality (VR) for

Pierre J Hoffmeyer

providing useful pedagogy. Developments in artificial intelligence, realistic image rendering and haptic feedback are moving forward at a rapid rate. Augmented and virtual reality will become essential learning tools to teach and to facilitate planning

Alan G. Fraser, Rob G.H.H. Nelissen, Per Kjærsgaard-Andersen, Piotr Szymański, Tom Melvin, Paul Piscoi, and On behalf of the CORE–MD Investigators (see Appendix)

.3 Developing guidance for the evaluation of artificial intelligence and standalone software in medical devices 2.4 Recommendations concerning high-risk medical devices in children Extracting maximal value from medical device registries and real

François Lintz, Cesar de Cesar Netto, Alexeij Barg, Arne Burssens, Martinus Richter, and Weight Bearing CT International Study Group

the same instruction in different ways, although this might be suppressed in the future by the use of artificial intelligence in imaging, where the observers are replacable by an AI algorithm. However, when this measurement is repeated on a document

Claus Varnum, Alma Bečić Pedersen, Ola Rolfson, Cecilia Rogmark, Ove Furnes, Geir Hallan, Keijo Mäkelä, Richard de Steiger, Martyn Porter, and Søren Overgaard

expect that every surgeon is updated on risk factors for revision and inferior outcome of THA. Moreover, it is not likely that clinicians can put all these data together and extrapolate the results. The use of artificial intelligence by extraction from

David Constantinescu, William Pavlis, Michael Rizzo, Dennis Vanden Berge, Spencer Barnhill, and Victor Hugo Hernandez

create predictive models that utilized sensor data from as early as 11 days postoperatively to successfully cluster patients into groups which correlated to 6-week PROMs. Thus, artificial intelligence with data from activity sensors in the perioperative

Benedikt J. Braun, Bernd Grimm, Andrew M. Hanflik, Meir T. Marmor, Peter H. Richter, Andrew K. Sands, and Sureshan Sivananthan

survival and mortality . Crit Care Med 2016 ; 44 : e1074 – e1081 . 32. Kim DH MacKinnon T . Artificial intelligence in fracture detection: transfer learning from deep convolutional neural networks . Clin Radiol 2018 ; 73

Habeeb Bishi, Joshua B V Smith, Vipin Asopa, Richard E Field, Chao Wang, and David H Sochart

. Value of 3D preoperative planning for primary total hip arthroplasty based on artificial intelligence technology . Journal of Orthopaedic Surgery and Research 2021 16 156. ( ) 20 Inoue D Kabata T Maeda