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        <title>Incorporating Figure Captions and Descriptive Text in MeSH Term Indexing</title>
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    <abstract>The goal of text classification is to automatically assign categories to documents. Deep learning automatically learns effective features from data instead of adopting human-designed features. In this paper, we focus specifically on biomedical document classification using a deep learning approach. We present a novel multichannel TextCNN model for MeSH term indexing. Beyond the normal use of the text from the abstract and title for model training, we also consider figure and table captions, as well as paragraphs associated with the figures and tables. We demonstrate that these latter text sources are important feature sources for our method. A new dataset consisting of these text segments curated from 257,590 full text articles together with the articles’ MEDLINE/PubMed MeSH terms is publicly available.</abstract>
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%0 Conference Proceedings
%T Incorporating Figure Captions and Descriptive Text in MeSH Term Indexing
%A Wang, Xindi
%A Mercer, Robert E.
%Y Demner-Fushman, Dina
%Y Cohen, Kevin Bretonnel
%Y Ananiadou, Sophia
%Y Tsujii, Junichi
%S Proceedings of the 18th BioNLP Workshop and Shared Task
%D 2019
%8 August
%I Association for Computational Linguistics
%C Florence, Italy
%F wang-mercer-2019-incorporating
%X The goal of text classification is to automatically assign categories to documents. Deep learning automatically learns effective features from data instead of adopting human-designed features. In this paper, we focus specifically on biomedical document classification using a deep learning approach. We present a novel multichannel TextCNN model for MeSH term indexing. Beyond the normal use of the text from the abstract and title for model training, we also consider figure and table captions, as well as paragraphs associated with the figures and tables. We demonstrate that these latter text sources are important feature sources for our method. A new dataset consisting of these text segments curated from 257,590 full text articles together with the articles’ MEDLINE/PubMed MeSH terms is publicly available.
%R 10.18653/v1/W19-5018
%U https://aclanthology.org/W19-5018
%U https://doi.org/10.18653/v1/W19-5018
%P 165-175

Markdown (Informal)

[Incorporating Figure Captions and Descriptive Text in MeSH Term Indexing](https://aclanthology.org/W19-5018) (Wang & Mercer, BioNLP 2019)

• Incorporating Figure Captions and Descriptive Text in MeSH Term Indexing (Wang & Mercer, BioNLP 2019)

ACL

• Xindi Wang and Robert E. Mercer. 2019. Incorporating Figure Captions and Descriptive Text in MeSH Term Indexing. In Proceedings of the 18th BioNLP Workshop and Shared Task, pages 165–175, Florence, Italy. Association for Computational Linguistics.