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

被引：0

作者：

Gao, Welting ^{[1
]}

Gao, Xiangyu ^{[1
]}

Chen, Wenjin ^{[2
]}

Foran, David J. ^{[2
]}

Chen, Yi ^{[1
]}

机构：

[1] New Jersey Inst Technol, Newark, NJ 07102 USA

[2] Rutgers State Univ, Rutgers Canc Inst New Jersey, Brunswick, NJ 08901 USA

来源：

ADVANCES IN KNOWLEDGE DISCOVERY AND DATA MINING, PT IV, PAKDD 2024 | 2024年 / 14648卷

基金：

美国国家卫生研究院; 美国国家科学基金会;

关键词：

Biomarker Extraction; Information Extraction; Aspect-Based Sentiment Analysis; Large Language Model; Attention Mechanism; Natural Language Processing;

D O I：

10.1007/978-981-97-2238-9_10

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

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.

引用

页码：129 / 141

页数：13

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