A machine learning approach to identify stride characteristics predictive of musculoskeletal injury, enforced rest and retirement in Thoroughbred racehorses
- DOI
- 10.1038/s41598-024-79071-1
- Published
- 2024-11-22
- Container
- Scientific Reports
- Publisher
- Springer Science and Business Media LLC
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1038/s41598-024-79071-1,
title = {A machine learning approach to identify stride characteristics predictive of musculoskeletal injury, enforced rest and retirement in Thoroughbred racehorses},
author = {Paulo M. Bogossian and Usha Nattala and Adelene S. M. Wong and Ashleigh V. Morrice-West and Geordie Z. Zhang and Pratibha Rana and R. Chris Whitton and Peta L. Hitchens},
year = {2024},
journal = {Scientific Reports},
doi = {10.1038/s41598-024-79071-1},
url = {https://doi.org/10.1038/s41598-024-79071-1}
}RIS
TY - JOUR TI - A machine learning approach to identify stride characteristics predictive of musculoskeletal injury, enforced rest and retirement in Thoroughbred racehorses AU - Paulo M. Bogossian AU - Usha Nattala AU - Adelene S. M. Wong AU - Ashleigh V. Morrice-West AU - Geordie Z. Zhang AU - Pratibha Rana AU - R. Chris Whitton AU - Peta L. Hitchens PY - 2024 JO - Scientific Reports DO - 10.1038/s41598-024-79071-1 UR - https://doi.org/10.1038/s41598-024-79071-1 ER -
APA
Bogossian, P. M., Nattala, U., Wong, A. S. M., Morrice-West, A. V., Zhang, G. Z., Rana, P., Whitton, R. C., & Hitchens, P. L. (2024). A machine learning approach to identify stride characteristics predictive of musculoskeletal injury, enforced rest and retirement in Thoroughbred racehorses. Scientific Reports. https://doi.org/10.1038/s41598-024-79071-1
Source records
- crossref · retrieved 2026-09-25T19:13:34.901Z