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Improving BERT-based Query-by-Document Retrieval with Multi-task Optimization Read chapter Read first chapter

2022 | OriginalPaper | Chapter

Medical Entity Linking in Laypersons’ Language

Author : Annisa Maulida Ningtyas

Published in: Advances in Information Retrieval

Publisher: Springer International Publishing

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Abstract

Due to the vast amount of health-related data on the Internet, a trend toward digital health literacy is emerging among laypersons. We hypothesize that providing trustworthy explanations of informal medical terms in social media can improve information quality. Entity linking (EL) is the task of associating terms with concepts (entities) in the knowledge base. The challenge with EL in lay medical texts is that the source texts are often written in loose and informal language. We propose an end-to-end entity linking approach that involves identifying informal medical terms, normalizing medical concepts according to SNOMED-CT, and linking entities to Wikipedia to provide explanations for laypersons.

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previous chapter Multimodal Retrieval in E-Commerce
next chapter A Topical Approach to Capturing Customer Insight Dynamics in Social Media
Footnotes
1
The paper was presented in Forum for Information Retrieval Evaluation (FIRE) 2021 conference.
 
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Metadata
Title
Medical Entity Linking in Laypersons’ Language
Author
Annisa Maulida Ningtyas
Copyright Year
2022
Book
Advances in Information Retrieval

Print ISBN: 978-3-030-99738-0

Electronic ISBN: 978-3-030-99739-7

Copyright Year: 2022

DOI
https://doi.org/10.1007/978-3-030-99739-7_63