Streamlining social media information retrieval for public health research with deep learning

Published: 01 Jan 2024, Last Modified: 13 Nov 2024J. Am. Medical Informatics Assoc. 2024EveryoneRevisionsBibTeXCC BY-SA 4.0
Abstract: Social media-based public health research is crucial for epidemic surveillance, but most studies identify relevant corpora with keyword-matching. This study develops a system to streamline the process of curating colloquial medical dictionaries. We demonstrate the pipeline by curating a Unified Medical Language System (UMLS)-colloquial symptom dictionary from COVID-19-related tweets as proof of concept.
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