Showing 1 - 5 results of 5 for search 'Jacobien H. F. Oosterhoff', query time: 0.03s
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Prediction of Postoperative Delirium in Geriatric Hip Fracture Patients: A Clinical Prediction Model Using Machine Learning Algorithms by Jacobien H. F. Oosterhoff MD, Aditya V. Karhade MD, MBA, Tarandeep Oberai PT, Esteban Franco-Garcia MD, Job N. Doornberg MD, PhD, Joseph H. Schwab MD, MS
Published 2021-12-01
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Developing a machine learning algorithm to predict the probability of aseptic loosening of the glenoid component after anatomical total shoulder arthroplasty: protocol for a retros... by Pascal Boileau, Michel P J van den Bekerom, Job N Doornberg, Laurent Lafosse, George S Athwal, Thibault Lafosse, Geert Alexander Buijze, Arno Alexander Macken, Loïc C Macken, Jacobien H F Oosterhoff
Published 2023-10-01
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Availability and reporting quality of external validations of machine-learning prediction models with orthopedic surgical outcomes: a systematic review by Olivier Q Groot, Bas J J Bindels, Paul T Ogink, Neal D Kapoor, Peter K Twining, Austin K Collins, Michiel E R Bongers, Amanda Lans, Jacobien H F Oosterhoff, Aditya V Karhade, Jorrit-Jan Verlaan, Joseph H Schwab
Published 2021-07-01
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A deep learning approach using an ensemble model to autocreate an image-based hip fracture registry by Jacobien H.F. Oosterhoff, MD, PhD, Soomin Jeon, PhD, Bardiya Akhbari, PhD, David Shin, BS, Daniel G. Tobert, MD, Synho Do, PhD, Soheil Ashkani-Esfahani, MD, Hamid Ghaednia, PhD, Joseph H. Schwab, MD, MS
Published 2024-01-01
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Development of machine-learning algorithms for 90-day and one-year mortality prediction in the elderly with femoral neck fractures based on the HEALTH and FAITH trials by Hidde Dijkstra, Jacobien H. F. Oosterhoff, Anouk van de Kuit, Frank F. A. IJpma, Joseph H. Schwab, Rudolf W. Poolman, Sheila Sprague, Sofia Bzovsky, Mohit Bhandari, Marc Swiontkowski, Emil H. Schemitsch, Job N. Doornberg, Laurent A. M. Hendrickx, On behalf of the Machine Learning Consortium, the HEALTH Investigators, and the FAITH Investigators
Published 2023-03-01
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