AIMC Topic: Athletic Injuries
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Robotic Assessment of Motor, Sensory, and Cognitive Function in Acute Sport-Related Concussion and Recovery.
Journal of neurotrauma
Sep 27, 2018
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
Jul 25, 2018
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
May 16, 2017
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
Feb 3, 2016
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
Jul 1, 2024
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...
Data scientists are predicting sports injuries with an algorithm.
Nature
Apr 1, 2021
A Machine Learning Approach to Assess Injury Risk in Elite Youth Football Players.
Medicine and science in sports and exercise
Aug 1, 2020
PURPOSE: To assess injury risk in elite-level youth football (soccer) players based on anthropometric, motor coordination and physical performance measures with a machine learning model.
Deep Learning for Detection of Complete Anterior Cruciate Ligament Tear.
Journal of digital imaging
Dec 1, 2019
Deep learning for MRI detection of sports injuries poses unique challenges. To address these difficulties, this study examines the feasibility and incremental benefit of several customized network architectures in evaluation of complete anterior cruc...
Machine Learning in Modeling High School Sport Concussion Symptom Resolve.
Medicine and science in sports and exercise
Jul 1, 2019
INTRODUCTION: Concussion prevalence in sport is well recognized, so too is the challenge of clinical and return-to-play management for an injury with an inherent indeterminant time course of resolve. A clear, valid insight into the anticipated resolu...
Using Machine Learning to Predict Lower-Extremity Injury in US Special Forces.
Medicine and science in sports and exercise
May 1, 2019
INTRODUCTION: Musculoskeletal injury rates in military personnel remain unacceptably high. Application of machine learning algorithms could be useful in multivariate models to predict injury in this population. The purpose of this study was to invest...
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