Measurement of Semantic Textual Similarity in Clinical Texts: Comparison of Transformer-Based Models.

ABSTRACT:

Background

Semantic textual similarity (STS) is one of the fundamental tasks in natural language processing (NLP). Many shared tasks and corpora for STS have been organized and curated in the general English domain; however, such resources are limited in the biomedical domain. In 2019, the National NLP Clinical Challenges (n2c2) challenge developed a comprehensive clinical STS dataset and organized a community effort to solicit state-of-the-art solutions for clinical STS.

Objective

This study presents our transformer-based clinical STS models developed during this challenge as well as new models we explored after the challenge. This project is part of the 2019 n2c2/Open Health NLP shared task on clinical STS.

Methods

In this study, we explored 3 transformer-based mode

SUBMITTER: Yang X 

PROVIDER: S-EPMC7721552 | biostudies-literature | 2020 Nov

REPOSITORIES: biostudies-literature