Artificial Intelligence for Sport Injury Prediction
Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review
Standard Standard
Artificial Intelligence in Sports, Movement and Health. ed. / Carlo Dindorf; Eva Bartaguiz; Freya Gassmann; Michael Fröhlich. 1. ed. Springer, 2024. p. 69-79.
Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review
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TY - CHAP
T1 - Artificial Intelligence for Sport Injury Prediction
AU - Owen, Robin
AU - Owen, Julian
AU - Evans, Seren
PY - 2024/9/2
Y1 - 2024/9/2
N2 - Preventing injury is a core facilitator of success in sport. Thus, vast sums of money are invested into achieving this. However, sport injury is still seen as equal parts 'art' and science. Despite the best efforts of individuals, teams, and national bodies to apply scientifically-derived injury prevention strategies, millions of athletes still get injured in sport every year. Evidently, sport injury prediction is a field which has scope for improvement. One potential way of advancing the field is the use of AI (artificial intelligence). It offers an opportunity to: (1) treat sporting injury as the complex phenomenon it appears to be; (2) consider the non-linear context surrounding athlete injuries; and (3) provide a supplement to practitioner reasoning, to facilitate quicker decisions. The present book chapter evaluates previous research studies' use of AI for injury prediction, assesses the unique advantages offered by AI-based analyses, and discusses challenges when attempting to utilise AI for injury prediction. Overall, the use of AI for sport injury prediction offers a fascinating opportunity. It may one day create a revolution in the field, improving not only prediction itself but also our understanding of the complex interactive factors which govern injury in sport.
AB - Preventing injury is a core facilitator of success in sport. Thus, vast sums of money are invested into achieving this. However, sport injury is still seen as equal parts 'art' and science. Despite the best efforts of individuals, teams, and national bodies to apply scientifically-derived injury prevention strategies, millions of athletes still get injured in sport every year. Evidently, sport injury prediction is a field which has scope for improvement. One potential way of advancing the field is the use of AI (artificial intelligence). It offers an opportunity to: (1) treat sporting injury as the complex phenomenon it appears to be; (2) consider the non-linear context surrounding athlete injuries; and (3) provide a supplement to practitioner reasoning, to facilitate quicker decisions. The present book chapter evaluates previous research studies' use of AI for injury prediction, assesses the unique advantages offered by AI-based analyses, and discusses challenges when attempting to utilise AI for injury prediction. Overall, the use of AI for sport injury prediction offers a fascinating opportunity. It may one day create a revolution in the field, improving not only prediction itself but also our understanding of the complex interactive factors which govern injury in sport.
KW - Artificial intelligence
KW - Sport injury
KW - Injury risk
KW - pattern recognition
KW - Machine learning
M3 - Chapter
SN - 978-3-031-67255-2
SN - 978-3-031-67258-3
SP - 69
EP - 79
BT - Artificial Intelligence in Sports, Movement and Health
A2 - Dindorf, Carlo
A2 - Bartaguiz, Eva
A2 - Gassmann, Freya
A2 - Fröhlich, Michael
PB - Springer
ER -