Surgical classification using natural language processing of informed consent forms in spine surgery.
Journal:
Neurosurgical focus
PMID:
37283446
Abstract
OBJECTIVE: In clinical spine surgery research, manually reviewing surgical forms to categorize patients by their surgical characteristics is a crucial yet time-consuming task. Natural language processing (NLP) is a machine learning tool used to adaptively parse and categorize important features from text. These systems function by training on a large, labeled data set in which feature importance is learned prior to encountering a previously unseen data set. The authors aimed to design an NLP classifier for surgical information that can review consent forms and automatically classify patients by the surgical procedure performed.