A review on deep neural networks for ICD coding

F Teng, Y Liu, T Li, Y Zhang, S Li… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
The International Classification of Diseases (ICD) is a standard for categorizing physical
conditions, which has been widely used for analyzing clinical data and monitoring health …

A unified review of deep learning for automated medical coding

S Ji, X Li, W Sun, H Dong, A Taalas, Y Zhang… - ACM Computing …, 2024 - dl.acm.org
Automated medical coding, an essential task for healthcare operation and delivery, makes
unstructured data manageable by predicting medical codes from clinical documents. Recent …

[HTML][HTML] Automated ICD coding for primary diagnosis via clinically interpretable machine learning

X Diao, Y Huo, S Zhao, J Yuan, M Cui, Y Wang… - International journal of …, 2021 - Elsevier
Background Computer-assisted clinical coding (CAC) based on automated coding
algorithms has been expected to improve the International Classification of Disease, tenth …

[HTML][HTML] Neural translation and automated recognition of ICD-10 medical entities from natural language: Model development and performance assessment

L Falissard, C Morgand, W Ghosn… - JMIR medical …, 2022 - medinform.jmir.org
Background: The recognition of medical entities from natural language is a ubiquitous
problem in the medical field, with applications ranging from medical coding to the analysis of …

[HTML][HTML] Retrieve and rerank for automated ICD coding via Contrastive Learning

K Niu, Y Wu, Y Li, M Li - Journal of Biomedical Informatics, 2023 - Elsevier
Automated ICD coding is a multi-label prediction task aiming at assigning patient diagnoses
with the most relevant subsets of disease codes. In the deep learning regime, recent works …

Comparison of different feature extraction methods for applicable automated ICD coding

Z Shuai, D **aolin, Y **g, H Yanni, C Meng… - BMC Medical Informatics …, 2022 - Springer
Background Automated ICD coding on medical texts via machine learning has been a hot
topic. Related studies from medical field heavily relies on conventional bag-of-words (BoW) …

Can current explainability help provide references in clinical notes to support humans annotate medical codes?

BH Kim, Z Deng, PS Yu, V Ganapathi - arxiv preprint arxiv:2210.15882, 2022 - arxiv.org
The medical codes prediction problem from clinical notes has received substantial interest in
the NLP community, and several recent studies have shown the state-of-the-art (SOTA) code …

[HTML][HTML] Automated ICD coding for coronary heart diseases by a deep learning method

S Zhao, X Diao, Y **a, Y Huo, M Cui, Y Wang, J Yuan… - Heliyon, 2023 - cell.com
Automated ICD coding via machine learning that focuses on some specific diseases has
been a hot topic. As one of the leading causes of death, coronary heart diseases (CHD) …

Modelling long medical documents and code associations for explainable automatic ICD coding

W Hou, X Wang, Y Wang, J Wang, F **ao - Expert Systems with …, 2024 - Elsevier
Abstract Quick and accurate International Classification of Diseases (ICD) code assignment
is vital for billing, reimbursement and medical research. Owing to the labour-intensive and …

Rare Codes Count: Mining Inter-code Relations for Long-tail Clinical Text Classification

J Chen, X Li, J **, L Yu, H **ong - Proceedings of the 5th Clinical …, 2023 - aclanthology.org
Multi-label clinical text classification, such as automatic ICD coding, has always been a
challenging subject in Natural Language Processing, due to its long, domain-specific …