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App. Res. of Comp. Accepted Paper
Vol. 43, 2026 No. 1

Symptom attribute classification method based on semantic graph-enhanced attention network

Jia Heming
Li Wei
Li Bo
Zhang Zhidong
State Key Laboratory of Extreme Environment Optoelectronic Dynamic Measurement Technology & Instrument, North University of China, Taiyuan 030003, China
DOI: 10.19734/j.issn.1001-3695.2025.06.0203

Abstract

Symptom attribute classification in medical dialogues plays a critical role in automatic diagnosis systems. The task aims to identify the attribute categories of symptoms described in dialogue texts. However, existing approaches often struggle to model long texts and fail to capture sufficient semantic dependencies, which limits their performance, especially on minority classes. To address these challenges, we propose a relation-aware graph attention network for symptom attribute classification. Our method integrates symptom-centered text segmentation, a fused encoding strategy, and a dependency-based relational graph attention mechanism to enhance contextual representations at multiple levels. We evaluate the approach on the CHIP-MDCFNPC dataset and achieve an F1 score of 72.13% and a macro-F1 of 77.94%, outperforming baseline models by 1.76% and 1.77%, respectively. The proposed method effectively improves symptom attribute classification in long medical dialogues and demonstrates particularly strong performance on minority classes, providing valuable insights for developing reliable automatic diagnostic systems.

Foundation Support

海南省重点研发计划(ZDYF2022SHFZ304)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2025.06.0203
Publish at: Application Research of Computers Accepted Paper, Vol. 43, 2026 No. 1

Publish History

[2025-09-17] Accepted Paper

Cite This Article

贾鹤鸣, 李伟, 李波, 等. 基于语义图增强注意力网络的症状属性分类方法 [J]. 计算机应用研究, 2026, 43 (1). (2025-09-17). https://doi.org/10.19734/j.issn.1001-3695.2025.06.0203. (Jia Heming, Li Wei, Li Bo, et al. Symptom attribute classification method based on semantic graph-enhanced attention network [J]. Application Research of Computers, 2026, 43 (1). (2025-09-17). https://doi.org/10.19734/j.issn.1001-3695.2025.06.0203. )

About the Journal

  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

Application Research of Computers has many high-level readers and authors, and its readers are mainly senior and middle-level researchers and engineers engaged in the field of computer science, as well as teachers and students majoring in computer science and related majors in colleges and universities. Over the years, the total citation frequency and Web download rate of Application Research of Computers have been ranked among the top of similar academic journals in this discipline, and the academic papers published are highly popular among the readers for their novelty, academics, foresight, orientation and practicality.

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