Team PolyU-CBSNLP at BioCreative-VII LitCovid Track: Ensemble Learning for COVID-19 Multilabel Classification

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Abstract

This paper briefly describes our works for the LitCovid shared task of BioCreative-VII Track 5. It is an ensemble learning-based system that utilized multiple biomedical pre-trained models. In particular, we leveraged seven advanced models for initialization with homogeneous and heterogenous structures through an ensemble bagging manner. To enhance the representation abilities, we further proposed to employ additional biomedical knowledge to facilitate ensemble learning. The experimental results on the LitCovid datasets show the effectiveness of our proposed approach.
Original languageEnglish
Title of host publicationProceedings of the BioCreative VII Challenge Evaluation Workshop
ISBN (Electronic)9780578323688
Publication statusPublished - 2 Nov 2021
EventBioCreative VII Challenge Evaluation Workshop - Online
Duration: 8 Nov 202110 Nov 2021

Workshop

WorkshopBioCreative VII Challenge Evaluation Workshop
Period8/11/2110/11/21

Keywords

  • COVID-19
  • LitCovid
  • Pre-trained Model
  • Deep Learning
  • Multilabel Classification
  • Ensemble Learning

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