Two hundred ninety-five injury descriptions from 135 consecutive patients treated at a level-1 trauma center were coded by three human coders (H1, H2, H3) and by TRI-CODE (T), a PC-based artificial intelligence software program.
Two study coders are nationally recognized experts who teach AIS coding for its developers (the Association for the Advancement of Automotive Medicine); the third has 5 years experience in ICD and AIS coding.
A « correct coding » (CC) was established for the study injury descriptions.
Coding results were obtained for each coder relative to the CC.
The correct ICD codes were selected in 96% of cases for H2, 92% for H1, 91% for T, and 86% for H3.
Mots-clés Pascal : Traumatisme, Homme, Indice gravité, Codage, Opérateur humain, Expert, Assistance ordinateur, Intelligence artificielle, Logiciel, Etude comparative, Précision
Mots-clés Pascal anglais : Trauma, Human, Severity score, Coding, Human operator, Expert, Computer aid, Artificial intelligence, Software, Comparative study, Accuracy
Notice produite par :
Inist-CNRS - Institut de l'Information Scientifique et Technique
Cote : 94-0445340
Code Inist : 002B16N. Création : 199406.