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Equine veterinary journal2022; 54(5); 844-846; doi: 10.1111/evj.13608

Science in brief: The Dorothy Havemeyer International Workshop on poor performance in horses: Recent advances in technology to improve monitoring and quantification.

Abstract: No abstract available
Publication Date: 2022-07-29 PubMed ID: 35905088DOI: 10.1111/evj.13608Google Scholar: Lookup
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  • Editorial

Cite This Article

APA
Navas de Solis C, Gabbett T, King MR, Keene R, McKenzie E. (2022). Science in brief: The Dorothy Havemeyer International Workshop on poor performance in horses: Recent advances in technology to improve monitoring and quantification. Equine Vet J, 54(5), 844-846. https://doi.org/10.1111/evj.13608

Publication

ISSN: 2042-3306
NlmUniqueID: 0173320
Country: United States
Language: English
Volume: 54
Issue: 5
Pages: 844-846

Researcher Affiliations

Navas de Solis, Cristobal
  • College of Veterinary Medicine, Clinical Studies New Bolton Center, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
Gabbett, Tim
  • Gabbett Performance Solutions, Brisbane, Queensland, Australia.
  • Centre for Health Research, University of Southern Queensland, Toowoomba, Queensland, Australia.
  • Institute of Health and Wellbeing, Federation University, Ballarat, Victoria, Australia.
King, Melissa R
  • Department of Clinical Sciences, Colorado State University, Fort Collins, Colorado, USA.
Keene, Robert
  • Boehringer Ingelheim Animal Health USA Inc, Duluth, Georgia, USA.
McKenzie, Erica
  • Department of Veterinary Clinical Sciences, Carlson College of Veterinary Medicine, Oregon State University, Corvallis, Oregon, USA.

MeSH Terms

  • Animals
  • Horse Diseases / diagnosis
  • Horses
  • Technology

References

This article includes 10 references
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Citations

This article has been cited 3 times.
  1. Siegers E, van Wijk E, van den Broek J, Sloet van Oldruitenborgh-Oosterbaan M, Munsters C. Longitudinal Training and Workload Assessment in Young Friesian Stallions in Relation to Fitness: Part 1. Animals (Basel) 2023 Feb 16;13(4).
    doi: 10.3390/ani13040689pubmed: 36830476google scholar: lookup
  2. Park T, Hong S, Murray L, Lee J, Shah A, Mesa JC, Lee H, Couetil L, Lee CH. Wearable smart textile band for continuous equine health monitoring. Biosens Bioelectron 2026 Jan 15;292:118073.
    doi: 10.1016/j.bios.2025.118073pubmed: 41076872google scholar: lookup
  3. Bogossian PM, Nattala U, Wong ASM, Morrice-West AV, Zhang GZ, Rana P, Whitton RC, Hitchens PL. A machine learning approach to identify stride characteristics predictive of musculoskeletal injury, enforced rest and retirement in Thoroughbred racehorses. Sci Rep 2024 Nov 22;14(1):28967.
    doi: 10.1038/s41598-024-79071-1pubmed: 39578597google scholar: lookup