Can Machine Learning Help Predict Knee Injuries

Machine learning algorithm cannot develop a sufficiently effective model to predict knee injuries in individual athletes.

Anterior cruciate ligament (ACL) injuries are common in team sports and cutting sports. Preventing them is important for both elite and amateur athletes. Multiple injury risk factors have been recognized in previous research, but the actual prediction of ACL injuries is still a matter of controversy.

Application of Machine Learning Algorithms to Treat ACL Injuries

The University of Jyväskylä’s Digital Health Intelligence Laboratory in collaboration with researchers from Norwegian school of sports sciences tried to predict the risk of ACL injury in individual athletes using machine learning.

Artificial Intelligence in Healthcare - An Overview
Artificial intelligence (AI) in healthcare is the discipline using data intensive computer based solutions to improve patient care and outcome.

‘The use of machine learning and data in sports and exercise applications is increasing rapidly and the results obtained now provide valuable insights into the opportunities and challenges for method development in this field.’

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"The result was statistically significant, but in practice the predictive ability is so low that it is not useful in practical clinical assessment of ACL injuries", says Susanne Jauhiainen, who conducted the study.

Nowadays, developing AI applications and conducting different experiments by using machine learning is relatively easy due to the usability and accessibility of tools. On the other hand, they also make it easy to produce promising prediction and classification models by chance.

"A central part of the study was also to develop a process that would ensure the quality and reliability of the results for comprehensive testing of AI models. This approach has already been applied in a previous injury study conducted with the UKK institute."

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The data used in the study is a part of the Norwegian School of Sports Sciences’ extensive injury research project and is the largest data set collected in the field.

The research data consisted of female handball and football professionals. The total number of studied athletes was 880.

Injuries Related to Sports
Injuries are common in the sporting world. They can be minor like bruises and cuts, serious like fractures and sometimes fatal like head injuries.

Despite the large and comprehensive data set and the use of various machine learning methods, the study could not predict ACL injuries well enough in practice.

"Even though we sort of failed this time, it can’t be said that machine learning and artificial intelligence can’t still predict injuries in the future. The result is useful because it will help injury researchers move towards collecting more relevant measurements", Jauhiainen concludes.

Sports Medicine
Sports medicine is a branch of medicine dealing with the diagnosis and treatment of sports injuries that result from strenuous activity or exercise.

Source-Eurekalert