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Jakub Olczak

Showing results (1-10 of 8) with videos related to

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Seminars in Cell & Developmental Biology|February 7, 2016
Evaluating network inference methods in terms of their ability to preserve the topology and complexity of genetic networksNarsis A Kiani, Hector Zenil, Jakub Olczak, et al.
Acta Orthopaedica|October 26, 2020
Ankle fracture classification using deep learning: automating detailed AO Foundation/Orthopedic Trauma Association (AO/OTA) 2018 malleolar fracture identification reaches a high degree of correct classificationJakub Olczak, Filip Emilson, Ali Razavian, et al.
BMC Musculoskeletal Disorders|October 4, 2024
External validation of an artificial intelligence multi-label deep learning model capable of ankle fracture classificationJakub Olczak, Jasper Prijs, Frank IJpma, et al.
Acta Orthopaedica|July 7, 2017
Artificial intelligence for analyzing orthopedic trauma radiographsJakub Olczak, Niklas Fahlberg, Atsuto Maki, et al.
Acta Orthopaedica|May 14, 2021
Presenting artificial intelligence, deep learning, and machine learning studies to clinicians and healthcare stakeholders: an introductory reference with a guideline and a Clinical AI Research (CAIR) checklist proposalJakub Olczak, John Pavlopoulos, Jasper Prijs, et al.
The Bone & Joint Journal|August 1, 2022
Artificial intelligence and computer vision in orthopaedic trauma : the why, what, and howJasper Prijs, Zhibin Liao, Soheil Ashkani-Esfahani, et al.
Bone & Joint Open|October 20, 2021
An increasing number of convolutional neural networks for fracture recognition and classification in orthopaedics : are these externally validated and ready for clinical application?Luisa Oliveira E Carmo, Anke van den Merkhof, Jakub Olczak, et al.
European Journal of Trauma and Emergency Surgery : Official Publication of the European Trauma Society|November 14, 2022
Development and external validation of automated detection, classification, and localization of ankle fractures: inside the black box of a convolutional neural network (CNN)Jasper Prijs, Zhibin Liao, Minh-Son To, et al.
Pageof 1

Showing results (1-10 of 8) with videos related to

Sort By:
Pageof 1
Seminars in Cell & Developmental Biology|February 7, 2016
Evaluating network inference methods in terms of their ability to preserve the topology and complexity of genetic networksNarsis A Kiani, Hector Zenil, Jakub Olczak, et al.
Acta Orthopaedica|October 26, 2020
Ankle fracture classification using deep learning: automating detailed AO Foundation/Orthopedic Trauma Association (AO/OTA) 2018 malleolar fracture identification reaches a high degree of correct classificationJakub Olczak, Filip Emilson, Ali Razavian, et al.
BMC Musculoskeletal Disorders|October 4, 2024
External validation of an artificial intelligence multi-label deep learning model capable of ankle fracture classificationJakub Olczak, Jasper Prijs, Frank IJpma, et al.
Acta Orthopaedica|July 7, 2017
Artificial intelligence for analyzing orthopedic trauma radiographsJakub Olczak, Niklas Fahlberg, Atsuto Maki, et al.
Acta Orthopaedica|May 14, 2021
Presenting artificial intelligence, deep learning, and machine learning studies to clinicians and healthcare stakeholders: an introductory reference with a guideline and a Clinical AI Research (CAIR) checklist proposalJakub Olczak, John Pavlopoulos, Jasper Prijs, et al.
The Bone & Joint Journal|August 1, 2022
Artificial intelligence and computer vision in orthopaedic trauma : the why, what, and howJasper Prijs, Zhibin Liao, Soheil Ashkani-Esfahani, et al.
Bone & Joint Open|October 20, 2021
An increasing number of convolutional neural networks for fracture recognition and classification in orthopaedics : are these externally validated and ready for clinical application?Luisa Oliveira E Carmo, Anke van den Merkhof, Jakub Olczak, et al.
European Journal of Trauma and Emergency Surgery : Official Publication of the European Trauma Society|November 14, 2022
Development and external validation of automated detection, classification, and localization of ankle fractures: inside the black box of a convolutional neural network (CNN)Jasper Prijs, Zhibin Liao, Minh-Son To, et al.
Pageof 1