Oral Presentation 24th International Conference of Racing Analysts and Veterinarians 2026

The risk of fatal musculoskeletal injury (FMI) can be determined by AI applications to IMU data collected during races (130401)

Warwick Bayly 1 , David Lambert 2 , Nicholas P Hall 1 , David Hawke 3 , Mikael Holmstroem 2
  1. College of Veterinary Medicine, Washington State University, Pullman, Washington, United States of America
  2. StrideSAFE, LLC, Midway, KY, United States
  3. StrideMASTER, Melbourne, Victoria, Australia

Background

              Hall et al. (manuscript available on request) used an expert AI system based on 42,631 starts by 15,779 horses including 144 races by 61 horses which suffered either a condylar or proximal sesamoid fracture to correctly identify >75% of potential fractures.

               Additional cases of fatal musculoskeletal injuries (FMI) were made available for modeling.

Objectives

  • Can an expert AI system use data from a single run to assess the overall risk for any FMI?
  • For an individual horse, can AI estimate the likelihood of FMI by using longitudinal data?

Methods

              Data was collected on 54,000 runs including 353 fracture runs of 157 horses with 15 different FMIs.

              A proprietary expert AI algorithm (StrideSAFE version 4.5) assigned a Risk Factor for each run on a scale of 1 to 500 (lowest to highest risk). For each horse a Risk Factor Average (RFA) was calculated using all runs over the previous 12-months.

Risk Factor ranges were used to define risk category ratings 1-5 where category 5 were at the highest risk.

Results

              Risk score category 1 was associated with 65% of starts. Other proportions were 20% category 2, 10% category 3, 3% category 4, and 2% category 5.

              RFA and FMI incidences were exponentially correlated (R2 = 0.95 p<0.001) 27.8% of 36 horses with a RFA>125 suffered FMIs compared to 7.7% of 78 horses with RFA 65-125 and <1% of horses with RFA<5.

Conclusion

              Only 2% of runs were category 5. To reduce FMI a category 5 run, particularly if involving a horse with a RFA>125, should receive a thorough clinical examination. Longitudinal data and the RFA may provide the most accurate assessment of FMI risk as horses with an RFA 126-500, had a >25% chance of FMI.