Improving the Quality of Suggestions for Medical Text Simplification Tools

AMIA Annu Symp Proc. 2022 May 23;2022:284-292. eCollection 2022.ABSTRACTText continues to be an important medium for communicating health-related information. We have built a text simplification tool that gives concrete suggestions on how to simplify health and medical texts. An important component of the tool identifies difficult words and suggests simpler synonyms based on pre-existing resources (WordNet and UMLS). These candidate substitutions are not always appropriate in all contexts. In this paper, we introduce a filtering algorithm that utilizes semantic similarity based on word embeddings to determine if the candidate substitution is appropriate in the context of the text. We provide an analysis of our approach on a new dataset of 788 labeled substitution examples. The filtering algorithm is particularly helpful at removing obvious examples and can improve the precision by 3% at a recall level of 95%.PMID:35854724 | PMC:PMC9285171

Source: AMIA Annual Symposium Proceedings - July 20, 2022 Category: Bioinformatics Authors: David Kauchak Jorge Apricio Gondy Leroy Source Type: research