JLAN: medical code prediction via joint learning attention networks and denoising mechanism

JLAN: medical code prediction via joint learning attention networks and denoising mechanism

Abstract Background Clinical notes are documents that contain detailed information about the health status of patients. Medical codes generally accompany them. However, the manual diagnosis is costly and error-prone. Moreover, large datasets in clinical diagnosis are susceptible to noise labels beca...

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Bibliographic Details
Main Authors: Xingwang Li, Yijia Zhang, Faiz ul Islam, Deshi Dong, Hao Wei, Mingyu Lu
Format: Article
Language:English
Published: BMC 2021-12-01
Series:BMC Bioinformatics
Subjects:
Automatic diagnosis
Attention mechanism
Denoising model
Joint learning
Multi-label classification
Online Access:https://doi.org/10.1186/s12859-021-04520-x

Internet

https://doi.org/10.1186/s12859-021-04520-x

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