AIMC Topic: Athletic Injuries

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A Random Forest Machine Learning Framework to Reduce Running Injuries in Young Triathletes.

Sensors (Basel, Switzerland)
BACKGROUND: The running segment of a triathlon produces 70% of the lower limb injuries. Previous research has shown a clear association between kinematic patterns and specific injuries during running.

New Machine Learning Approach for Detection of Injury Risk Factors in Young Team Sport Athletes.

International journal of sports medicine
The purpose of this article is to present how predictive machine learning methods can be utilized for detecting sport injury risk factors in a data-driven manner. The approach can be used for finding new hypotheses for risk factors and confirming the...

Motion Sensors-Based Machine Learning Approach for the Identification of Anterior Cruciate Ligament Gait Patterns in On-the-Field Activities in Rugby Players.

Sensors (Basel, Switzerland)
Anterior cruciate ligament (ACL) injuries are common among athletes. Despite a successful return to sport (RTS) for most of the injured athletes, a significant proportion do not return to competitive levels, and thus RTS post ACL reconstruction still...

Using machine learning to improve our understanding of injury risk and prediction in elite male youth football players.

Journal of science and medicine in sport
OBJECTIVES: The purpose of this study was to examine whether the use of machine learning improved the ability of a neuromuscular screen to identify injury risk factors in elite male youth football players.

Robotic Assessment of Motor, Sensory, and Cognitive Function in Acute Sport-Related Concussion and Recovery.

Journal of neurotrauma
There is a need for better tools to objectively, reliably, and precisely assess neurological function after sport-related concussion (SRC). The aim of this study was to use a robotic device (Kinesiological Instrument for Normal and Altered Reaching M...

Effective injury forecasting in soccer with GPS training data and machine learning.

PloS one
Injuries have a great impact on professional soccer, due to their large influence on team performance and the considerable costs of rehabilitation for players. Existing studies in the literature provide just a preliminary understanding of which facto...

Defining a multimodal signature of remote sports concussions.

The European journal of neuroscience
Sports-related concussions lead to persistent anomalies of the brain structure and function that interact with the effects of normal ageing. Although post-mortem investigations have proposed a bio-signature of remote concussions, there is still no cl...

Computerized "Learn-As-You-Go" classification of traumatic brain injuries using NEISS narrative data.

Accident; analysis and prevention
One important routine task in injury research is to effectively classify injury circumstances into user-defined categories when using narrative text. However, traditional manual processes can be time consuming, and existing batch learning systems can...

Optimizing Concussion Care Seeking: Using Machine Learning to Predict Delayed Concussion Reporting.

The American journal of sports medicine
BACKGROUND: Early medical attention after concussion may minimize symptom duration and burden; however, many concussions are undiagnosed or have a delay in diagnosis after injury. Many concussion symptoms (eg, headache, dizziness) are not visible, me...