Application of natural language processing to post-structuring of rectal cancer MRI reports

We applied natural language processing (NLP) to the extraction of relevant information from MRI reports of rectal cancer written in Chinese. We used 358 MRI reports written between 2015 and 2021 to develop a rule-based NLP model to extract 11 key image features. The accuracy, precision, recall, and F1 score of our NLP model for correct extraction of values from reports were 93.82%, 95.63%, 87.06%, and 91.15% for pre-2015 reports, and 92.55%, 98.53%, 94.15%, and 96.29% for post-2021 reports. Our NLP system with rule-based pattern matching realized the rapid and accurate structured processing of rectal cancer MRI reports.