Validation of a Machine Learning Brain Electrical Activity–Based Index to Aid in Diagnosing Concussion Among Athletes
This study suggests that, as an objective, and reliable indicator of the presence of concussive brain injury and readiness for return to activity, the Concussion Index has the potential to aid in clinical diagnosis and reduce long term concussion-related disability.
Emergency Department Triage of Traumatic Head Injury Using Brain Electrical Activity Biomarkers: A Multisite Prospective Observational Validation Trial
Using EEG-based biomarker, high accuracy of predicting the likelihood of being CT+ was obtained, with high NPV and sensitivity to any traumatic bleeding and to hematomas. Specificity was significantly higher than standard CT decision rules.
JAMA Highlights Success of BrainScope's EEG-based Concussion Index As Reliable Indicator of Concussion
JAMA Network Open has published "Validation of a Machine Learning Brain Electrical Activity-Based Index to Aid in Diagnosing Concussion Among Athletes," a ground-breaking study on the accuracy of the BrainScope FDA-cleared biomarker, the Concussion Index, to indicate the likelihood and severity of concussive brain injury and to aid in evaluating an athlete's readiness to return to play.
BrainScope Wins BioHealth Capital Region 5th Annual Crab Trap Competition
BrainScope, a medical neurotechnology company that is a pioneer in the use of A.I. and machine learning in the creation of biomarkers of brain injuries and disease, was selected from five finalists as the company with the most commercial potential at the 5th Annual BioHealth Capital Region Crab Trap Competition
• Ages 18 – 85 years for structural brain injury • Ages 13 – 85 years for functional brain injury • Glasgow Coma Scale (GCS) 13 – 15 • Within 72 hours of injury, at baseline, and over time • Suitable for alcohol/drug impaired & patients on blood thinners