Fine-tuning a pre-trained Transformers-based model for gene name entity recognition in biomedical text using a customized dataset: case of Desulfovibrio vulgaris Hildenborough-Reference-Cited by-同舟云学术

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Fine-tuning a pre-trained Transformers-based model for gene name entity recognition in biomedical text using a customized dataset: case of Desulfovibrio vulgaris Hildenborough

Published:2023-12-05 Issue: Volume: Page:4473-4479
ISSN:
Container-title:2023 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)
language:
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Author:

Bomgni Alain Bertrand¹,Abdala Dialo²,Shrestha Gurung Bichar Dip¹,Julius Nkenlifack Marcellin²,Gadhamshetty Venkataramana³,Etienne Gnimpieba Z.¹

Affiliation:

1. University of South Dakota,Dept. of Biomedical Engineering,Vermillion,SD,USA

2. University of Dschang,Dept. of Computer Science,Dschang,Cameroon

3. South Dakota School of Mines and Technology,Dept. of Civil and Environmental Engineering,Rapid City,SD,USA

Funder

National Science Foundation

Health

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10385250/10385251/10385403.pdf?arnumber=10385403

Reference16 articles.

1. SciBERT: A Pretrained Language Model for Scientific Text

2. Attention model-based and multi-organism driven gene recognition from text: application to a microbial biofilm organism set

3. GenNER - A highly scalable and optimal NER method for text-based gene and protein recognition

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