Zobrazeno 1 - 10
of 686
pro vyhledávání: '"Injury prediction"'
Autor:
Afxentios Kekelekis, Rabiu Muazu Musa, Pantelis T. Nikolaidis, Filipe Manuel Clemente, Eleftherios Kellis
Publikováno v:
Muscles, Vol 3, Iss 3, Pp 297-309 (2024)
Despite ongoing efforts, the relationship between groin strength and injury remains unclear. The challenge of accurately predicting injuries presents an opportunity for researchers to develop prevention strategies to reduce the occurrence of such inj
Externí odkaz:
https://doaj.org/article/551e1be9193b465f939fec97f0a29dfe
Autor:
Yu Wang, Yiwei Liang, Guangjun Wang, Tao Wang, Shu Xu, Xianjun Yang, Yining Sun, Zenghui Ding
Publikováno v:
PeerJ Computer Science, Vol 10, p e2177 (2024)
A meniscus injury is a prevalent condition affecting the knee joint. The construction of a subjective prediction model for meniscus injury represents a potentially invaluable diagnostic tool for physicians. Nevertheless, given the variability of path
Externí odkaz:
https://doaj.org/article/3b3ca8cc387441e0966a8f265e99c8b7
Autor:
Jarosław Domaradzki
Publikováno v:
Symmetry, Vol 16, Iss 10, p 1390 (2024)
Morphological and functional asymmetry of the lower limbs is a well-recognized factor contributing to musculoskeletal injuries among athletes across different levels. However, limited research exists on evaluating foot mobility asymmetry as a potenti
Externí odkaz:
https://doaj.org/article/2a45489d91df41c6aba340f5f8d29c96
Autor:
Jarosław Domaradzki
Publikováno v:
Symmetry, Vol 16, Iss 7, p 876 (2024)
Biological measurements that predict injury risk are crucial diagnostic tools. Yet, research on improving diagnostic accuracy in detecting accidents is insufficient. Combining multiple predictors and assessing them via ROC curves can enhance this acc
Externí odkaz:
https://doaj.org/article/3988edbebdd4482c8edb041f7f29cae5
Autor:
Nikolaos I. Liveris, Charis Tsarbou, George Papageorgiou, Elias Tsepis, Konstantinos Fousekis, Joanna Kvist, Sofia A. Xergia
Publikováno v:
Applied Sciences, Vol 14, Iss 14, p 6316 (2024)
There is a gap in the literature regarding the complex interrelationships among hamstring injury (HI) risk factors. System dynamics (SD) modeling is considered an appropriate approach for understanding the complex etiology of HI for effective injury
Externí odkaz:
https://doaj.org/article/f08e40d5dd8b4fb2b8d59b9c8c0ccb5a
Publikováno v:
Frontiers in Neuroscience, Vol 18 (2024)
IntroductionExercise is pivotal for maintaining physical health in contemporary society. However, improper postures and movements during exercise can result in sports injuries, underscoring the significance of skeletal motion analysis. This research
Externí odkaz:
https://doaj.org/article/aa532242ee344f55b1fd0791101b22bf
Publikováno v:
Frontiers in Neuroscience, Vol 17 (2023)
IntroductionIn this study, we explore the potential benefits of integrating natural cognitive systems (medical professionals' expertise) and artificial cognitive systems (deep learning models) in the realms of medical image analysis and sports injury
Externí odkaz:
https://doaj.org/article/4ea25e6551f145bc87b4aed996296e0f
Autor:
Rocío Elizabeth Duarte Ayala, David Pérez Granados, Carlos Alberto González Gutiérrez, Mauricio Alberto Ortega Ruíz, Natalia Rojas Espinosa, Emanuel Canto Heredia
Publikováno v:
Applied Sciences, Vol 14, Iss 2, p 570 (2024)
This innovative study addresses the prevalent issue of sports injuries, particularly focusing on ankle injuries, utilizing advanced analytical tools such as artificial intelligence (AI) and machine learning (ML). Employing a logistic regression model
Externí odkaz:
https://doaj.org/article/fd23065437864bebbcb71c979e105242
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Akademický článek
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