Zobrazeno 1 - 10
of 145
pro vyhledávání: '"Christophe Ley"'
Publikováno v:
BMC Medical Research Methodology, Vol 24, Iss 1, Pp 1-8 (2024)
Abstract Introduction While there is an interest in defining longitudinal change in people with chronic illness like Parkinson’s disease (PD), statistical analysis of longitudinal data is not straightforward for clinical researchers. Here, we aim t
Externí odkaz:
https://doaj.org/article/c2f841074f3344948c24ae0ca330899b
Publikováno v:
Chaos, Solitons & Fractals: X, Vol 13, Iss , Pp 100115- (2024)
This study aims to identify the types of lineups based on their topological structure within a lineup network and to explore the relationship between lineup types and team standings during 10 NBA playoff seasons from 2012-2013 season to 2021-2022 sea
Externí odkaz:
https://doaj.org/article/c135f41511094a7b908dca4b3c80d9f3
Autor:
Felix C. Oettl, Ayoosh Pareek, Philipp W. Winkler, Bálint Zsidai, James A. Pruneski, Eric Hamrin Senorski, Sebastian Kopf, Christophe Ley, Elmar Herbst, Jacob F. Oeding, Alberto Grassi, Michael T. Hirschmann, Volker Musahl, Kristian Samuelsson, Thomas Tischer, Robert Feldt, ESSKA Artificial Intelligence Working Group
Publikováno v:
Journal of Experimental Orthopaedics, Vol 11, Iss 3, Pp n/a-n/a (2024)
Abstract Artificial intelligence's (AI) accelerating progress demands rigorous evaluation standards to ensure safe, effective integration into healthcare's high‐stakes decisions. As AI increasingly enables prediction, analysis and judgement capabil
Externí odkaz:
https://doaj.org/article/1af373a9ad784a31a99c0d570ab45c80
Autor:
Bálint Zsidai, Janina Kaarre, Eric Narup, Eric Hamrin Senorski, Ayoosh Pareek, Alberto Grassi, Christophe Ley, Umile Giuseppe Longo, Elmar Herbst, Michael T. Hirschmann, Sebastian Kopf, Romain Seil, Thomas Tischer, Kristian Samuelsson, Robert Feldt, ESSKA Artificial Intelligence Working Group
Publikováno v:
Journal of Experimental Orthopaedics, Vol 11, Iss 3, Pp n/a-n/a (2024)
Abstract Recent advances in artificial intelligence (AI) present a broad range of possibilities in medical research. However, orthopaedic researchers aiming to participate in research projects implementing AI‐based techniques require a sound unders
Externí odkaz:
https://doaj.org/article/5089200bb05a408cba1ad24463e5de7f
Autor:
Karsten Hollander, David Blanco, Pascal Edouard, Laurent Navarro, Antoine Bruneau, Alexis Ruffault, Joris Chapon, Pierre-Eddy Dandrieux, Christophe Ley
Publikováno v:
BMJ Open, Vol 13, Iss 5 (2023)
Introduction Two-thirds of athletes (65%) have at least one injury complaint leading to participation restriction (ICPR) in athletics (track and field) during one season. The emerging practice of medicine and public health supported by electronic pro
Externí odkaz:
https://doaj.org/article/6db6758213ca489785bf8e3e8d70ba00
Autor:
Bálint Zsidai, Ann‐Sophie Hilkert, Janina Kaarre, Eric Narup, Eric Hamrin Senorski, Alberto Grassi, Christophe Ley, Umile Giuseppe Longo, Elmar Herbst, Michael T. Hirschmann, Sebastian Kopf, Romain Seil, Thomas Tischer, Kristian Samuelsson, Robert Feldt, ESSKA Artificial Intelligence Working Group
Publikováno v:
Journal of Experimental Orthopaedics, Vol 10, Iss 1, Pp n/a-n/a (2023)
Abstract Artificial intelligence (AI) has the potential to transform medical research by improving disease diagnosis, clinical decision‐making, and outcome prediction. Despite the rapid adoption of AI and machine learning (ML) in other domains and
Externí odkaz:
https://doaj.org/article/57eee3a661f84e70946421fecdace9e5
Autor:
Bálint Zsidai, Janina Kaarre, Ann‐Sophie Hilkert, Eric Narup, Eric Hamrin Senorski, Alberto Grassi, Olufemi R. Ayeni, Volker Musahl, Christophe Ley, Elmar Herbst, Michael T. Hirschmann, Sebastian Kopf, Romain Seil, Thomas Tischer, Kristian Samuelsson, Robert Feldt, ESSKA Artificial Intelligence Working Group
Publikováno v:
Journal of Experimental Orthopaedics, Vol 10, Iss 1, Pp n/a-n/a (2023)
Externí odkaz:
https://doaj.org/article/f69ae336a76b448bb2a3d1a12bcc5ec8
Publikováno v:
PLoS ONE, Vol 18, Iss 1, p e0278599 (2023)
Economic and financial crises are characterised by unusually large events. These tail events co-move because of linear and/or nonlinear dependencies. We introduce TailCoR, a metric that combines (and disentangles) these linear and non-linear dependen
Externí odkaz:
https://doaj.org/article/68a636d36bfd4847974a7eca113487ba
Publikováno v:
Frontiers in Big Data, Vol 4 (2022)
This paper presents Bayesian directional data modeling via the skew-rotationally-symmetric Fisher-von Mises-Langevin (FvML) distribution. The prior distributions for the parameters are a pivotal building block in Bayesian analysis, therefore, the imp
Externí odkaz:
https://doaj.org/article/c66942d5ceef43fe8ccca64f9edf9c33
Publikováno v:
Journal of Experimental Orthopaedics, Vol 8, Iss 1, Pp n/a-n/a (2021)
Abstract Purpose Injuries are common in sports and can have significant physical, psychological and financial consequences. Machine learning (ML) methods could be used to improve injury prediction and allow proper approaches to injury prevention. The
Externí odkaz:
https://doaj.org/article/117b308e526f4b298100f588ead0d7a8