App. Res. of Comp. Accepted Paper
Vol. 41, 2024 No. 9

Few-shot ICD automatic coding method based on prompt learning and hypersphere prototypes

Xu Chun
Ji Shuangyan
Ma Zhilong
School of Information Management, Xinjiang University of Finance & Economics, Urumqi 830012, China
DOI: 10.19734/j.issn.1001-3695.2024.01.0031

Abstract

To address the issue of weak model generalization caused by processing long texts, hierarchical coding structures, and long-tailed distributions in International Classification of Diseases (ICD) automatic coding methods, this paper proposed the Hypersphere Prototypical with Prompt learning (PromptHP) method for few-shot ICD automatic coding, leveraging medical pre-trained language models. Firstly, the PromptHP method combined coding descriptions and clinical texts into the prompt template to improve the model's comprehension of clinical texts. Then, it utilized the pre-trained language model's prior knowledge for initial prediction. Next, it introduced the hypersphere prototypical onto the output representation of the pre-trained language model for category modeling and metric classification, while fine-tuning the network on the medical dataset to incorporate the data knowledge and improve the model's performance on few-shot ICD coding classification tasks. Finally, it obtained the coding prediction results by integrating and weighting the two parts of the prediction results. Experimental results on the publicly available medical dataset MIMIC-III demonstrate that PromptHP outperforms state-of-the-art baseline methods, increasing the Macro-AUC, Micro-AUC, Macro-F1, and Micro-F1 of few-shot coding by 1.77%, 1.54%, 14.22%, and 15.01%, respectively. The experimental results validate the effectiveness of the PromptHP method in few-shot coding classification tasks.

Foundation Support

国家自然科学基金项目(62266041)
新疆自然科学基金项目(2023D01A73)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2024.01.0031
Publish at: Application Research of Computers Accepted Paper, Vol. 41, 2024 No. 9

Publish History

[2024-05-14] Accepted Paper

Cite This Article

徐春, 吉双焱, 马志龙. 基于提示学习和超球原型的小样本ICD自动编码方法 [J]. 计算机应用研究, 2024, 41 (9). (2024-05-14). https://doi.org/10.19734/j.issn.1001-3695.2024.01.0031. (Xu Chun, Ji Shuangyan, Ma Zhilong. Few-shot ICD automatic coding method based on prompt learning and hypersphere prototypes [J]. Application Research of Computers, 2024, 41 (9). (2024-05-14). https://doi.org/10.19734/j.issn.1001-3695.2024.01.0031. )

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  • Application Research of Computers Monthly Journal
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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.

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