mlsanityData to 7 Oct 2026

MedDec: A Dataset for Extracting Medical Decisions from Discharge Summaries

arXiv 2408.12980 ↗First posted 23 Aug 2024cs.CL cs.LGcited by 4

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Abstract (arXiv)

Medical decisions directly impact individuals' health and well-being. Extracting decision spans from clinical notes plays a crucial role in understanding medical decision-making processes. In this paper, we develop a new dataset called "MedDec", which contains clinical notes of eleven different phenotypes (diseases) annotated by ten types of medical decisions. We introduce the task of medical decision extraction, aiming to jointly extract and classify different types of medical decisions within clinical notes. We provide a comprehensive analysis of the dataset, develop a span detection model as a baseline for this task, evaluate recent span detection approaches, and employ a few metrics to measure the complexity of data samples. Our findings shed light on the complexities inherent in clinical decision extraction and enable future work in this area of research. The dataset and code are available through https://github.com/CLU-UML/MedDec.

Key facts. Cited by 4 papers in the map (data through 7 Oct 2026). Builds on 29 of its 66 references that are in the map. First posted on arXiv 23 Aug 2024.

Builds on

29 of 66 references.

References · 29

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17 more
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Cited by year (2026 to 7 Oct)

Citing papers per year: 2026: 4.

4 papers.

  1. 2026Three Generations of Healthcare IT: From the Digital Record to the Computable Care Processcited by 1
  2. 2026Linguistic Blind Spots in Clinical Decision Extractioncited by 0
  3. 2026Systematic Evaluation of Large Language Models for Post-Discharge Clinical Action Extractioncited by 0
  4. 2026PrionNER: A Named Entity Recognition Dataset for Prion Disease Biomedical Literaturecited by 0