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Related Experiment Video

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Collection and Extraction of Saliva DNA for Next Generation Sequencing
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Sequence tagging for biomedical extractive question answering.

Wonjin Yoon1, Richard Jackson2, Aron Lagerberg3

  • 1Department of Computer Science and Engineering, Korea University, Seoul 02841, South Korea.

Bioinformatics (Oxford, England)
|June 17, 2022
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Summary
This summary is machine-generated.

Biomedical question answering often requires multiple answers, unlike general EQA. This study introduces a novel multi-span extraction approach for biomedical EQA, outperforming existing models.

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Area of Science:

  • Biomedical Informatics
  • Natural Language Processing
  • Computational Biology

Background:

  • Current extractive question answering (EQA) models primarily focus on single-span extraction, suitable for general domain questions.
  • Biomedical EQA (BioEQA) models have adopted this single-span approach, often requiring post-processing steps.

Purpose of the Study:

  • To investigate the answer type distribution in biomedical questions compared to general domain questions.
  • To develop a BioEQA model capable of handling multi-span (list-type) answers effectively.
  • To address the limitations of single-span extraction in the biomedical domain.

Main Methods:

  • A comparative analysis of question-answer distributions across general and biomedical domains.
  • Development of a sequence tagging approach for multi-span extraction in BioEQA.
  • Directly modeling questions with a variable number of answer phrases without post-processing.

Main Results:

  • Biomedical questions are significantly more likely to require list-type (multiple) answers than factoid-type (single) answers.
  • The proposed sequence tagging approach for BioEQA achieved superior performance on list-type questions in the BioASQ 7b and 8b datasets.
  • The model successfully learned to determine the number of answers directly from training data, eliminating the need for post-processing.

Conclusions:

  • The single-span extraction setting is insufficient for comprehensive BioEQA.
  • A multi-span extraction approach, such as the proposed sequence tagging method, is essential for effectively answering biomedical questions.
  • The developed BioEQA model offers improved accuracy and efficiency for list-type biomedical question answering.