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Algorithm Research & Explore
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App. Res. of Comp. Printed Article
Vol. 41, 2024 No. 8
2315-2321

CT-JIE: collaborative Transformer for joint information extraction from patient-doctor dialogues

Lin Zhizhong
Wang Huazhen
School of Computer Science & Technology, Huaqiao University, Xiamen Fujian 361000, China
DOI: 10.19734/j.issn.1001-3695.2023.12.0591

Abstract

Addressing the challenges of capturing the correlation between information extraction tasks and the contextual information in doctor-patient dialogues during electronic medical record construction, this paper proposed a Transformer-based collaborative information extraction method called CT-JIE(collaborative Transformer for joint information extraction). Firstly, this method utilized a sliding window combined with Bi-LSTM to acquire historical information from the dialogues and employed a label-aware module to capture task-related information in the dialogue context. Secondly, the global attention module enhanced the model's ability to perceive the context of symptom entities and their status. Finally, the interactive guidance module explicitly modeled the interaction among intent recognition, slot filling, and status recognition tasks to capture the complex contexts and relationships among multiple tasks. Experiments demonstrate that this method outperforms other baseline and ablation models on the IMCS21 and CMDD datasets, showing strong generalization ability and performance advantages in handling joint information extraction tasks.

Foundation Support

装备预研教育部联合基金资助项目(8091B022150)
福建省社会科学基金基础研究项目(FJ2021B110)
厦门市重大科技计划资助项目(3502Z20221021)
厦门市一般科技资助项目(3502Z20226037)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2023.12.0591
Publish at: Application Research of Computers Printed Article, Vol. 41, 2024 No. 8
Section: Algorithm Research & Explore
Pages: 2315-2321
Serial Number: 1001-3695(2024)08-010-2315-07

Publish History

[2024-03-01] Accepted Paper
[2024-08-05] Printed Article

Cite This Article

林致中, 王华珍. 基于Transformer交互指导的医患对话联合信息抽取方法 [J]. 计算机应用研究, 2024, 41 (8): 2315-2321. (Lin Zhizhong, Wang Huazhen. CT-JIE: collaborative Transformer for joint information extraction from patient-doctor dialogues [J]. Application Research of Computers, 2024, 41 (8): 2315-2321. )

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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