mlsanityData to 14 Oct 2026

MDACE: MIMIC Documents Annotated with Code Evidence

arXiv 2307.03859 ↗First posted 7 Jul 2023cs.CLcited by 19

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Abstract (arXiv)

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 Coding (CAC) which has improved significantly in recent years, thanks to advances in machine learning technologies. Yet simply predicting a set of final codes for a patient encounter is insufficient as CAC systems are required to provide supporting textual evidence to justify the billing codes. A model able to produce accurate and reliable supporting evidence for each code would be a tremendous benefit. However, a human annotated code evidence corpus is extremely difficult to create because it requires specialized knowledge. In this paper, we introduce MDACE, the first publicly available code evidence dataset, which is built on a subset of the MIMIC-III clinical records. The dataset -- annotated by professional medical coders -- consists of 302 Inpatient charts with 3,934 evidence spans and 52 Profee charts with 5,563 evidence spans. We implemented several evidence extraction methods based on the EffectiveCAN model (Liu et al., 2021) to establish baseline performance on this dataset. MDACE can be used to evaluate code evidence extraction methods for CAC systems, as well as the accuracy and interpretability of deep learning models for multi-label classification. We believe that the release of MDACE will greatly improve the understanding and application of deep learning technologies for medical coding and document classification.

Key facts. Cited by 19 papers in the map (data through 14 Oct 2026). Builds on 20 of its 43 references that are in the map. First posted on arXiv 7 Jul 2023.

Builds on

20 of 43 references.

References · 20

  1. 2017Squeeze-and-Excitation Networkscited by 4,789
  2. 2018FEVER: a large-scale dataset for Fact Extraction and VERificationcited by 1,375
  3. 2018e-SNLI: Natural Language Inference with Natural Language Explanationscited by 468
  4. 2018Explainable Prediction of Medical Codes from Clinical Textcited by 234
  5. 2021Teach Me to Explain: A Review of Datasets for Explainable Natural Language Processingcited by 126
  6. 2019Inferring Which Medical Treatments Work from Reports of Clinical Trialscited by 64
  7. 2022Code Synonyms Do Matter: Multiple Synonyms Matching Network for Automatic ICD Codingcited by 53
  8. 2022PLM-ICD: Automatic ICD Coding with Pretrained Language Modelscited by 49
  9. 2021Understanding Interlocking Dynamics of Cooperative Rationalizationcited by 36
  10. 2020Inferring Degrees from Incomplete Networks and Nonlinear Dynamicscited by 33
  11. 2022A Unified Review of Deep Learning for Automated Medical Codingcited by 26
  12. 2021Towards BERT-based Automatic ICD Coding: Limitations and Opportunitiescited by 25
8 more
  1. 2019Fine-grained Sentiment Analysis with Faithful Attentioncited by 23
  2. 2021Read, Attend, and Code: Pushing the Limits of Medical Codes Prediction from Clinical Notes by Machinescited by 23
  3. 2020Weakly- and Semi-supervised Evidence Extractioncited by 16
  4. 2020Experimental Evaluation and Development of a Silver-Standard for the MIMIC-III Clinical Coding Datasetcited by 15
  5. 2022Hierarchical Label-wise Attention Transformer Model for Explainable ICD Codingcited by 13
  6. 2021Thermostat: A Large Collection of NLP Model Explanations and Analysis Toolscited by 11
  7. 2021An Explainable CNN Approach for Medical Codes Prediction from Clinical Textcited by 9
  8. 2022Entity Anchored ICD Codingcited by 3

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Citing papers per year: 2023: 1; 2024: 5; 2025: 8; 2026: 5.

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  1. 2024Exploring LLM Multi-Agents for ICD Codingcited by 14
  2. 2024An Unsupervised Approach to Achieve Supervised-Level Explainability in Healthcare Recordscited by 12
  3. 2025Code Like Humans: A Multi-Agent Solution for Medical Codingcited by 11
  4. 2023Surpassing GPT-4 Medical Coding with a Two-Stage Approachcited by 6
  5. 2024Aligning AI Research with the Needs of Clinical Coding Workflows: Eight Recommendations Based on US Data Analysis and Critical Reviewcited by 5
  6. 2024MedDec: A Dataset for Extracting Medical Decisions from Discharge Summariescited by 4
  7. 2025The Anatomy of Evidence: An Investigation Into Explainable ICD Codingcited by 3
  8. 2025MedDCR: Learning to Design Agentic Workflows for Medical Codingcited by 3
  9. 2024Continuous Predictive Modeling of Clinical Notes and ICD Codes in Patient Health Recordscited by 1
  10. 2025Explainable ICD Coding via Entity Linkingcited by 1
  11. 2025Evaluation and LLM-Guided Learning of ICD Coding Rationalescited by 1
  12. 2025Complete Evidence Extraction with Model Ensembles: A Case Study on Medical Codingcited by 1
7 more
  1. 2026Symphony for Medical Coding: A Next-Generation Agentic System for Scalable and Explainable Medical Codingcited by 1
  2. 2025RDMA: Cost Effective Agent-Driven Rare Disease Mining from Electronic Health Recordscited by 0
  3. 2025Predictive Multimodal Modeling of Diagnoses and Treatments in EHRcited by 0
  4. 2026From Documents to Spans: Span-Centric Learning for LLM-based Explainable Medical Codingcited by 0
  5. 2026Bridging the Version Gap: Multi-version Training Improves ICD Code Prediction, Especially for Rare Codescited by 0
  6. 2026MedicalBench: Evaluating Large Language Models Toward Improved Medical Concept Extractioncited by 0
  7. 2026Enhancing LLM Medical Coding with Structured External Knowledgecited by 0