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BioReX: Biomarker Information Extraction Inspired by Aspect-Based Sentiment Analysis

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Advances in Knowledge Discovery and Data Mining (PAKDD 2024)

Abstract

Biomarkers are critical in cancer diagnosis, prognosis, and treatment planning. However, this information is often buried in unstructured text form. In this paper, we make an analogy between Biomarker Information Extraction and Aspect-Based Sentiment Analysis. We propose a system, Biomarker and Result Extraction Model (BioReX). BioReX employs BERT post-training methods to augment the BioBERT model with domain-specific and task-specific knowledge for biomarker extraction. It uses syntactic-based and semantic-based attention to associate results to corresponding biomarkers. Evaluation demonstrates the effectiveness of the proposed approach.

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Notes

  1. 1.

    https://github.com/NJIT-AI-in-Healthcare/Pathology-Biomarker-Information-Extraction.

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Acknowledgment

The work is partially supported by a grant from the National Institutes of Health (UL1TR003017), the Martin Tuchman’62 Chair Endowment, the Leir Foundation, and the National Science Foundation (CNS 2237328). We gratefully acknowledge Nancy Sazo, Huiqi Chu, and Evita Sadimin for medical knowledge support.

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Correspondence to Yi Chen .

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Gao, W., Gao, X., Chen, W., Foran, D.J., Chen, Y. (2024). BioReX: Biomarker Information Extraction Inspired by Aspect-Based Sentiment Analysis. In: Yang, DN., Xie, X., Tseng, V.S., Pei, J., Huang, JW., Lin, J.CW. (eds) Advances in Knowledge Discovery and Data Mining. PAKDD 2024. Lecture Notes in Computer Science(), vol 14648. Springer, Singapore. https://doi.org/10.1007/978-981-97-2238-9_10

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  • DOI: https://doi.org/10.1007/978-981-97-2238-9_10

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-97-2240-2

  • Online ISBN: 978-981-97-2238-9

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