TraumaICD Bidirectional Encoder Representation From Transformers: A Natural Language Processing Algorithm to Extract Injury International Classification of Diseases, 10th Edition Diagnosis Code From Free Text.

Objective: To develop and validate TraumaICDBERT, a natural language processing algorithm to predict injury International Classification of Diseases, 10th edition (ICD-10) diagnosis codes from trauma tertiary survey notes.

Background: The adoption of ICD-10 diagnosis codes in clinical settings for injury prediction is hindered by the lack of real-time availability. Existing natural language processing algorithms have limitations in accurately predicting injury ICD-10 diagnosis codes.