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. 2022 May 26;38(11):3136-3138.
doi: 10.1093/bioinformatics/btac298.

Simulation and annotation of global acronyms

Maxim Filimonov  1 , Daphné Chopard  1 , Irena Spasić  1
Affiliations

Simulation and annotation of global acronyms

Maxim Filimonov et al. Bioinformatics. .

Abstract

Motivation: Global acronyms are used in written text without their formal definitions. This makes it difficult to automatically interpret their sense as acronyms tend to be ambiguous. Supervised machine learning approaches to sense disambiguation require large training datasets. In clinical applications, large datasets are difficult to obtain due to patient privacy. Manual data annotation creates an additional bottleneck.

Results: We proposed an approach to automatically modifying scientific abstracts to (i) simulate global acronym usage and (ii) annotate their senses without the need for external sources or manual intervention. We implemented it as a web-based application, which can create large datasets that in turn can be used to train supervised approaches to word sense disambiguation of biomedical acronyms.

Availability and implementation: The datasets will be generated on demand based on a user query and will be downloadable from https://datainnovation.cardiff.ac.uk/acronyms/.

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Figures

Fig. 1.
Fig. 1.
System design
See this image and copyright information in PMC

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