title: A comparison of a decision tree induction algorithm with the ACS guidelines for trauma triage.
abstract: Triage is a key component of trauma care. Unfortunately, mistriage rates remain high. Machine learning techniques have the potential to improve triage. Our experiment showed that while decision tree induction was as accurate as the most widely accepted trauma triage guidelines, they performed differently with respect to over- and undertriage.
authors.affiliation: School of Nursing, University of Central Florida, Orlando, FL, USA.
authors.forename: Steve
authors.initials: S
authors.lastname: Talbert
authors.forename: Douglas A
authors.initials: DA
authors.lastname: Talbert
mesh_terms: D000293:Adolescent; D000328:Adult; D000465:Algorithms; D001185:Artificial Intelligence; D003663:Decision Trees; D006801:Humans; D015601:Injury Severity Score; D009657:North Carolina; D017410:Practice Guidelines as Topic; D014218:Triage / Q000379:methods*; D014947:Wounds and Injuries / Q000628:therapy*