document: Use of natural language processing to translate clinical information from a database of 889,921 chest radiographic reports The aim was to evaluate translation of chest radiographic reports using natural language processing and to compare the findings with those in the literature . A natural language processor coded 10 years of narrative chest radiographic reports from an urban academic medical center . Coding for 150 reports was compared with manual coding . Frequencies and cooccurrences of 24 clinical conditions -LRB- diseases , abnormalities , and clinical states -RRB- were estimated . The ratio of right to left lung mass , association of pleural effusion with other conditions , and frequency of bullet and stab wounds were compared with independent observations . The sensitivity and specificity of the system 's pneumothorax coding were compared with those of manual financial coding . Internal and external validation in this study confirmed the accuracy of natural language processing for translating chest radiographic narrative reports into a large database of information
doc_bio_tags: O O B I I O O O O O O O O O O O O O O O O O O O O O O O B I I O O O O O O O O O O O O O O O O O O O O O O O O O B I I I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O B I O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O B I I O O O O O O O O O O O O
extractive_keyphrases: natural language processing urban academic medical center pleural effusion stab wounds pneumothorax coding
abstractive_keyphrases: chest radiographic report database clinical information translation clinical condition frequency clinical condition cooccurrence right to left lung mass ratio bullet wounds