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

There is no objec­tive stan­dard for the diag­no­sis of mild trau­mat­ic brain injury (con­cus­sion), which remains a diag­no­sis based large­ly on the patient’s sub­jec­tive report of signs and symp­toms. Accu­rate objec­tive iden­ti­fi­ca­tion of the pres­ence and sever­i­ty of con­cus­sion and the assess­ment of the readi­ness to return to activ­i­ty present sig­nif­i­cant clin­i­cal chal­lenges to health care pro­fes­sion­als. Chil­dren, ado­les­cents, and young adults are par­tic­u­lar­ly at risk because sig­nif­i­cant brain devel­op­ment con­tin­ues through­out these years. The lack of, or delay in, con­cus­sion diag­no­sis has been shown to be asso­ci­at­ed with much slow­er recov­ery,1-3 may be asso­ci­at­ed with aca­d­e­m­ic or cog­ni­tive and emo­tion­al func­tion­ing,4-6 and has been asso­ci­at­ed with impaired adult func­tion­ing in those sus­tain­ing con­cus­sive injury before the age of 25 years.7

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