Detecting Redundancy in Electronic Medical Records Using Clinical BERT
Semantic Textual Similarity (STS) computes the degree of semantic equivalence between text snippets. STS is used in various natural language processing tasks, including detecting redundant information in texts. Although STS tasks have been widely studied in the general English domain, there exists very few resources for STS tasks in the clinical domain. The methods used for general domain STS tasks might not work well in the clinical domain because of variability of natural language expressions, and clinical domain expressions are different from general domain expressions. We present a Clinical BERT based model for redundancy detection in clinical texts. Our experiments show that domain specific BERT improves performance of the model.