A unified review of deep learning for automated medical coding

S Ji, X Li, W Sun, H Dong, A Taalas, Y Zhang… - ACM Computing …, 2022 - 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 …

A comprehensive review of generative AI in healthcare

Y Shokrollahi, S Yarmohammadtoosky… - arXiv preprint arXiv …, 2023 - arxiv.org
The advancement of Artificial Intelligence (AI) has catalyzed revolutionary changes across
various sectors, notably in healthcare. Among the significant developments in this field are …

Attention-based multimodal fusion with contrast for robust clinical prediction in the face of missing modalities

J Liu, D Capurro, A Nguyen, K Verspoor - Journal of Biomedical Informatics, 2023 - Elsevier
Objective: With the increasing amount and growing variety of healthcare data, multimodal
machine learning supporting integrated modeling of structured and unstructured data is an …

Few-shot ICD coding with knowledge transfer and evidence representation

F Teng, Q Zhang, X Zhou, J Hu, T Li - Expert Systems with Applications, 2024 - Elsevier
The task of automatic ICD (International Classification of Diseases) coding involves
allocating appropriate ICD codes to electronic health records. Due to the long-tailed …

[HTML][HTML] Automated ICD coding using extreme multi-label long text transformer-based models

L Liu, O Perez-Concha, A Nguyen, V Bennett… - Artificial Intelligence in …, 2023 - Elsevier
Encouraged by the success of pretrained Transformer models in many natural language
processing tasks, their use for International Classification of Diseases (ICD) coding tasks is …

A two-stage decoder for efficient icd coding

TT Nguyen, V Schlegel, A Kashyap… - arXiv preprint arXiv …, 2023 - arxiv.org
Clinical notes in healthcare facilities are tagged with the International Classification of
Diseases (ICD) code; a list of classification codes for medical diagnoses and procedures …

Explainable text-tabular models for predicting mortality risk in companion animals

J Burton, S Farrell, PJ Mäntylä Noble… - Scientific Reports, 2024 - nature.com
As interest in using machine learning models to support clinical decision-making increases,
explainability is an unequivocal priority for clinicians, researchers and regulators to …

MDACE: MIMIC Documents Annotated with Code Evidence

H Cheng, R Jafari, A Russell, R Klopfer, E Lu… - arXiv preprint arXiv …, 2023 - arxiv.org
We introduce a dataset for evidence/rationale extraction on an extreme multi-label
classification task over long medical documents. One such task is Computer-Assisted …

CoRelation: Boosting Automatic ICD Coding Through Contextualized Code Relation Learning

J Luo, X Wang, J Wang, A Chang, Y Wang… - arXiv preprint arXiv …, 2024 - arxiv.org
Automatic International Classification of Diseases (ICD) coding plays a crucial role in the
extraction of relevant information from clinical notes for proper recording and billing. One of …

An automatic icd coding network using partition-based label attention

D Kim, H Yoo, S Kim - arXiv preprint arXiv:2211.08429, 2022 - arxiv.org
International Classification of Diseases (ICD) is a global medical classification system which
provides unique codes for diagnoses and procedures appropriate to a patient's clinical …