Medical Code Prediction
15 papers with code • 7 benchmarks • 7 datasets
Context: Prediction of medical codes from clinical notes is both a practical and essential need for every healthcare delivery organization within current medical systems. Automating annotation will save significant time and excessive effort by human coders today. A new milestone will mark a meaningful step toward fully Autonomous Medical Coding in machines reaching parity with human coders' performance in medical code prediction.
Question: What exactly is the medical code prediction problem?
Answer: Clinical notes contain much information about what precisely happened during the patient's entire stay. And those clinical notes (e.g., discharge summary) is typically long, loosely structured, consists of medical domain language, and sometimes riddled with spelling errors. So, it's a highly multi-label classification problem, and the forthcoming ICD-11 standard will add more complexity to the problem! The medical code prediction problem is to annotate this clinical note with multiple codes subset from nearly 70K total codes (in the current ICD-10 system, for example).
Benchmarks
These leaderboards are used to track progress in Medical Code Prediction
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Libraries
Use these libraries to find Medical Code Prediction models and implementationsDatasets
MIMIC-III
MIMIC-IV ICD-10
Latest papers
Automated Medical Coding on MIMIC-III and MIMIC-IV: A Critical Review and Replicability Study
joakimedin/medical-coding-reproducibility
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Medical coding is the task of assigning medical codes to clinical free-text documentation.
Knowledge Injected Prompt Based Fine-tuning for Multi-label Few-shot ICD Coding
whaleloops/KEPT
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Automatic International Classification of Diseases (ICD) coding aims to assign multiple ICD codes to a medical note with average length of 3, 000+ tokens.
HiCu: Leveraging Hierarchy for Curriculum Learning in Automated ICD Coding
wren93/hicu-icd
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One of the challenges in curriculum learning is the design of curricula -- i. e., in the sequential design of tasks that gradually increase in difficulty.
Code Synonyms Do Matter: Multiple Synonyms Matching Network for Automatic ICD Coding
ganjinzero/icd-msmn
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ACL 2022
Automatic ICD coding is defined as assigning disease codes to electronic medical records (EMRs).
Multitask Balanced and Recalibrated Network for Medical Code Prediction
VRCMF/MT-RAM
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Nevertheless, automated medical coding is still challenging because of the imbalanced class problem, complex code association, and noise in lengthy documents.
Modeling Diagnostic Label Correlation for Automatic ICD Coding
MiuLab/ICD-Correlation
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NAACL 2021
To address this problem, we propose a two-stage framework to improve automatic ICD coding by capturing the label correlation.
Medical Code Prediction from Discharge Summary: Document to Sequence BERT using Sequence Attention
HeoTaksung/Document-to-Sequence-BERT
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So we propose a model based on bidirectional encoder representations from transformers (BERT) using the sequence attention method for automatic ICD code assignment.
Multitask Recalibrated Aggregation Network for Medical Code Prediction
VRCMF/MT-RAM
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Medical coding translates professionally written medical reports into standardized codes, which is an essential part of medical information systems and health insurance reimbursement.
An Explainable CNN Approach for Medical Codes Prediction from Clinical Text
HeoTaksung/Document-to-Sequence-BERT
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Our approach substantially outperforms previous results on top-50 medical code prediction on MIMIC-III dataset.
Explainable Automated Coding of Clinical Notes using Hierarchical Label-wise Attention Networks and Label Embedding Initialisation
acadTags/Explainable-Automated-Medical-Coding
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LE initialisation consistently boosted most deep learning models for automated medical coding.
