ICDBigBird: A Contextual Embedding Model for ICD Code Classification

04/21/2022
by   George Michalopoulos, et al.
0

The International Classification of Diseases (ICD) system is the international standard for classifying diseases and procedures during a healthcare encounter and is widely used for healthcare reporting and management purposes. Assigning correct codes for clinical procedures is important for clinical, operational, and financial decision-making in healthcare. Contextual word embedding models have achieved state-of-the-art results in multiple NLP tasks. However, these models have yet to achieve state-of-the-art results in the ICD classification task since one of their main disadvantages is that they can only process documents that contain a small number of tokens which is rarely the case with real patient notes. In this paper, we introduce ICDBigBird a BigBird-based model which can integrate a Graph Convolutional Network (GCN), that takes advantage of the relations between ICD codes in order to create 'enriched' representations of their embeddings, with a BigBird contextual model that can process larger documents. Our experiments on a real-world clinical dataset demonstrate the effectiveness of our BigBird-based model on the ICD classification task as it outperforms the previous state-of-the-art models.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
06/15/2021

Medical Code Prediction from Discharge Summary: Document to Sequence BERT using Sequence Attention

Clinical notes are unstructured text generated by clinicians during pati...
research
10/24/2018

Clinical Concept Extraction with Contextual Word Embedding

Automatic extraction of clinical concepts is an essential step for turni...
research
06/24/2022

Classifying Unstructured Clinical Notes via Automatic Weak Supervision

Healthcare providers usually record detailed notes of the clinical care ...
research
06/13/2019

Interpretable ICD Code Embeddings with Self- and Mutual-Attention Mechanisms

We propose a novel and interpretable embedding method to represent the i...
research
10/01/2021

BERT4GCN: Using BERT Intermediate Layers to Augment GCN for Aspect-based Sentiment Classification

Graph-based Aspect-based Sentiment Classification (ABSC) approaches have...
research
02/26/2021

A Meta-embedding-based Ensemble Approach for ICD Coding Prediction

International Classification of Diseases (ICD) are the de facto codes us...
research
02/14/2020

Understanding patient complaint characteristics using contextual clinical BERT embeddings

In clinical conversational applications, extracted entities tend to capt...

Please sign up or login with your details

Forgot password? Click here to reset