mlsanityData to 7 Oct 2026

The RareDis corpus: a corpus annotated with rare diseases, their signs and symptoms

arXiv 2108.01204 ↗First posted 2 Aug 2021cs.CL cs.LGcited by 11

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Abstract (arXiv)

The RareDis corpus contains more than 5,000 rare diseases and almost 6,000 clinical manifestations are annotated. Moreover, the Inter Annotator Agreement evaluation shows a relatively high agreement (F1-measure equal to 83.5% under exact match criteria for the entities and equal to 81.3% for the relations). Based on these results, this corpus is of high quality, supposing a significant step for the field since there is a scarcity of available corpus annotated with rare diseases. This could open the door to further NLP applications, which would facilitate the diagnosis and treatment of these rare diseases and, therefore, would improve dramatically the quality of life of these patients.

Key facts. Cited by 11 papers in the map (data through 7 Oct 2026). Builds on 3 of its 66 references that are in the map. First posted on arXiv 2 Aug 2021.

Builds on

3 of 66 references.

References · 3

  1. 2019BioBERT: a pre-trained biomedical language representation model for biomedical text miningcited by 1,935
  2. 2020LUKE: Deep Contextualized Entity Representations with Entity-aware Self-attentioncited by 326
  3. 2018CollaboNet: collaboration of deep neural networks for biomedical named entity recognitioncited by 10

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 1; 2022: 1; 2023: 2; 2024: 3; 2025: 3; 2026: 1.

11 papers.

  1. 2022Wojood: Nested Arabic Named Entity Corpus and Recognition using BERTcited by 32
  2. 2023Identifying and Extracting Rare Disease Phenotypes with Large Language Modelscited by 18
  3. 2024Large Language Models Struggle in Token-Level Clinical Named Entity Recognitioncited by 7
  4. 2021Exploring deep learning methods for recognizing rare diseases and their clinical manifestations from textscited by 6
  5. 2024Evaluating Large Language Models for Public Health Classification and Extraction Taskscited by 6
  6. 2024AutoRD: An Automatic and End-to-End System for Rare Disease Knowledge Graph Construction Based on Ontologies-enhanced Large Language Modelscited by 3
  7. 2023Comparison of pipeline, sequence-to-sequence, and GPT models for end-to-end relation extraction: experiments with the rare disease use-casecited by 2
  8. 2025Decoding Rarity: Large Language Models in the Diagnosis of Rare Diseasescited by 0
  9. 2025RDMA: Cost Effective Agent-Driven Rare Disease Mining from Electronic Health Recordscited by 0
  10. 2025Leveraging Large Language Models for Rare Disease Named Entity Recognitioncited by 0
  11. 2026An artificial intelligence framework for end-to-end rare disease phenotyping from clinical notes using large language modelscited by 0