@article{ref1,
title="Predicting risk of sport-related concussion in collegiate athletes and military cadets: a machine learning approach using baseline data from the CARE Consortium  Study",
journal="Sports medicine",
year="2020",
author="Castellanos, Joel and Phoo, Cheng Perng and Eckner, James T. and Franco, Lea and Broglio, Steven P. and McCrea, Mike and McAllister, Thomas and Wiens, Jenna",
volume="ePub",
number="ePub",
pages="ePub-ePub",
abstract="OBJECTIVE: To develop a predictive model for sport-related concussion in collegiate  athletes and military service academy cadets using baseline data collecting during  the pre-participation examination. <br><br>METHODS: Baseline assessments were performed in  15,682 participants from 21 US academic institutions and military service academies  participating in the CARE Consortium Study during the 2015-2016 academic year. Participants were monitored for sport-related concussion during the subsequent  season. 176 baseline covariates mapped to 957 binary features were used as input  into a support vector machine model with the goal of learning to stratify  participants according to their risk for sport-related concussion. Performance was  evaluated in terms of area under the receiver operating characteristic curve (AUROC)  on a held-out test set. Model inputs significantly associated with either increased  or decreased risk were identified. <br><br>RESULTS: 595 participants (3.79%) sustained a  concussion during the study period. The predictive model achieved an AUROC of 0.73  (95% confidence interval 0.70-0.76), with variable performance across sports. Features with significant positive and negative associations with subsequent  sport-related concussion were identified. <br><br>CONCLUSION(S): This predictive model using  only baseline data identified athletes and cadets who would go on to sustain  sport-related concussion with comparable accuracy to many existing concussion  assessment tools for identifying concussion. Furthermore, this study provides  insight into potential concussion risk and protective factors.<p /> <p>Language: en</p>",
language="en",
issn="0112-1642",
doi="10.1007/s40279-020-01390-w",
url="http://dx.doi.org/10.1007/s40279-020-01390-w"
}