A Novel ICD Coding Method Based on Associated and Hierarchical Code Description Distillation

Fuente: arXiv
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Main Authors: Zhang, Bin, Wang, Junli
Format: Preprint
Published: 2024
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author Zhang, Bin
Wang, Junli
author_facet Zhang, Bin
Wang, Junli
contents ICD(International Classification of Diseases) coding involves assigning ICD codes to patients visit based on their medical notes. ICD coding is a challenging multilabel text classification problem due to noisy medical document inputs. Recent advancements in automated ICD coding have enhanced performance by integrating additional data and knowledge bases with the encoding of medical notes and codes. However, most of them ignore the code hierarchy, leading to improper code assignments. To address these problems, we propose a novel framework based on associated and hierarchical code description distillation (AHDD) for better code representation learning and avoidance of improper code assignment.we utilize the code description and the hierarchical structure inherent to the ICD codes. Therefore, in this paper, we leverage the code description and the hierarchical structure inherent to the ICD codes. The code description is also applied to aware the attention layer and output layer. Experimental results on the benchmark dataset show the superiority of the proposed framework over several state-of-the-art baselines.
format Preprint
id arxiv_https___arxiv_org_abs_2404_11132
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle A Novel ICD Coding Method Based on Associated and Hierarchical Code Description Distillation
Zhang, Bin
Wang, Junli
Computation and Language
ICD(International Classification of Diseases) coding involves assigning ICD codes to patients visit based on their medical notes. ICD coding is a challenging multilabel text classification problem due to noisy medical document inputs. Recent advancements in automated ICD coding have enhanced performance by integrating additional data and knowledge bases with the encoding of medical notes and codes. However, most of them ignore the code hierarchy, leading to improper code assignments. To address these problems, we propose a novel framework based on associated and hierarchical code description distillation (AHDD) for better code representation learning and avoidance of improper code assignment.we utilize the code description and the hierarchical structure inherent to the ICD codes. Therefore, in this paper, we leverage the code description and the hierarchical structure inherent to the ICD codes. The code description is also applied to aware the attention layer and output layer. Experimental results on the benchmark dataset show the superiority of the proposed framework over several state-of-the-art baselines.
title A Novel ICD Coding Method Based on Associated and Hierarchical Code Description Distillation
topic Computation and Language
url https://arxiv.org/abs/2404.11132