# HieNet: Bidirectional Hierarchy Framework for Automated ICD Coding

arXiv: https://arxiv.org/abs/2212.04891 · HTML: https://mlsanity.com/paper/2212.04891/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- Builds on 17 of its 34 references that are in the map.
- First posted on arXiv 9 Dec 2022.

## Builds on (most cited first, 17 of 17)

- [Adam: A Method for Stochastic Optimization](https://mlsanity.com/paper/1412.6980/) (2014)
- [Semi-Supervised Classification with Graph Convolutional Networks](https://mlsanity.com/paper/1609.02907/) (2016)
- [Efficient Estimation of Word Representations in Vector Space](https://mlsanity.com/paper/1301.3781/) (2013)
- [Predict then Propagate: Graph Neural Networks meet Personalized PageRank](https://mlsanity.com/paper/1810.05997/) (2018)
- [Language Modeling with Gated Convolutional Networks](https://mlsanity.com/paper/1612.08083/) (2016)
- [Explainable Prediction of Medical Codes from Clinical Text](https://mlsanity.com/paper/1802.05695/) (2018)
- [A Transformer-based Approach for Source Code Summarization](https://mlsanity.com/paper/2005.00653/) (2020)
- [A Convolutional Attention Network for Extreme Summarization of Source Code](https://mlsanity.com/paper/1602.03001/) (2016)
- [ICD Coding from Clinical Text Using Multi-Filter Residual Convolutional Neural Network](https://mlsanity.com/paper/1912.00862/) (2019)
- [Multimodal Machine Learning for Automated ICD Coding](https://mlsanity.com/paper/1810.13348/) (2018)
- [Multi-Label Classification of Patient Notes a Case Study on ICD Code Assignment](https://mlsanity.com/paper/1709.09587/) (2017)
- [Towards Automated ICD Coding Using Deep Learning](https://mlsanity.com/paper/1711.04075/) (2017)
- [Inferring Degrees from Incomplete Networks and Nonlinear Dynamics](https://mlsanity.com/paper/2004.10546/) (2020)
- [Attentive Pooling Networks](https://mlsanity.com/paper/1602.03609/) (2016)
- [Improving Palliative Care with Deep Learning](https://mlsanity.com/paper/1711.06402/) (2017)
- [Dilated Convolutional Attention Network for Medical Code Assignment from Clinical Text](https://mlsanity.com/paper/2009.14578/) (2020)
- [From Sentiment Annotations to Sentiment Prediction through Discourse Augmentation](https://mlsanity.com/paper/2011.03021/) (2020)

## Built on by (most cited first, 3 of 3)

- [Can GPT-3.5 Generate and Code Discharge Summaries?](https://mlsanity.com/paper/2401.13512/) (2024)
- [GE-Blender: Graph-Based Knowledge Enhancement for Blender](https://mlsanity.com/paper/2301.12850/) (2023)
- [Emotion Detection in Unfix-length-Context Conversation](https://mlsanity.com/paper/2302.06029/) (2023)

## Abstract (arXiv)

International Classification of Diseases (ICD) is a set of classification codes for medical records. Automated ICD coding, which assigns unique International Classification of Diseases codes with each medical record, is widely used recently for its efficiency and error-prone avoidance. However, there are challenges that remain such as heterogeneity, label unbalance, and complex relationships between ICD codes. In this work, we proposed a novel Bidirectional Hierarchy Framework(HieNet) to address the challenges. Specifically, a personalized PageRank routine is developed to capture the co-relation of codes, a bidirectional hierarchy passage encoder to capture the codes' hierarchical representations, and a progressive predicting method is then proposed to narrow down the semantic searching space of prediction. We validate our method on two widely used datasets. Experimental results on two authoritative public datasets demonstrate that our proposed method boosts state-of-the-art performance by a large margin.