Validation of a Machine Learning Brain Electrical Activity-Based Index to Aid in Diagnosing Concussion Among Athletes.

ABSTRACT:

Importance

An objective, reliable indicator of the presence and severity of concussive brain injury and of the readiness for the return to activity has the potential to reduce concussion-related disability.

Objective

To validate the classification accuracy of a previously derived, machine learning, multimodal, brain electrical activity-based Concussion Index in an independent cohort of athletes with concussion.

Design, setting, and participants

This prospective diagnostic cohort study was conducted at 10 clinical sites (ie, US universities and high schools) between February 4, 2017, and March 20, 2019. A cohort comprising a consecutive sample of 207 athletes aged 13 to 25 years with concussion and 373 matched athlete controls without concussion were assessed with elec

SUBMITTER: Bazarian JJ 

PROVIDER: S-EPMC7885039 | biostudies-literature | 2021 Feb

REPOSITORIES: biostudies-literature