README.md

metadata

license: cc-by-nc-4.0
dataset_info:
  features:
    - name: SOURCE
      dtype: string
    - name: TARGET
      dtype: string
  splits:
    - name: train
      num_bytes: 1724952
      num_examples: 5000
  download_size: 913357
  dataset_size: 1724952

Dataset Card for CLARA-MeD-5000

Table of Contents

• Table of Contents
• Dataset Description
  • Dataset Summary
  • Supported Tasks and Leaderboards
  • Languages
• Dataset Structure
  • Data Instances
  • Data Fields
• Dataset Creation
  • Source Data
  • Annotations
  • Personal and Sensitive Information
• Additional Information
  • Dataset Curators
  • Licensing Information
  • Citation Information
  • Contributions

Dataset Description

• Homepage: https://clara-nlp.uned.es/home/med/
• Repositories: https://github.com/lcampillos/CLARA-MeD, https://digital.csic.es/handle/10261/269887
• Paper: http://journal.sepln.org/sepln/ojs/ojs/index.php/pln/article/view/6439
• DOI: https://doi.org/10.20350/digitalCSIC/14644
• Point of Contact: Leonardo Campillos-Llanos

Dataset Summary

A parallel corpus with 5000 sentence pairs of professional and laymen variants as a benchmark for medical text simplification. This dataset was collected in the CLARA-MeD project, with the goal of simplifying medical texts in the Spanish language and reducing the language barrier to patient's informed decision making.

The corpus gathers 2 subsets:

• 3800 parallel sentences (149 862 tokens) semi-automatically aligned and revised by linguists.
• 1200 parallel sentences (144 019 tokens) manually simplified by linguists.

Supported Tasks and Leaderboards

Medical text simplification

Languages

Spanish

Dataset Structure

Data Instances

For each instance, there is a string for the source text (professional version), and a string for the target text (simplified version).

{'SOURCE': 'Varones mayores de 18 años, diagnosticados de alopecia androgénica grados I-IV de Sinclair, que no estén realizando ningún tratamiento capilar en la actualidad ni lo hayan realizado en los últimos 3 meses.'
 'TARGET': 'Hombres mayores de 18 años, diagnosticados de alopecia androgénica (calvicie) grados I-IV de Sinclair. Estos hombres no estarán realizando ningún tratamiento para el cabello en la actualidad ni lo habrán realizado en los últimos 3 meses.'}

Data Fields

• SOURCE: a string containing the professional version.
• TARGET: a string containing the simplified version.

Dataset Creation

Source Data

Who are the source language producers?

1. Drug leaflets and summaries of product characteristics from CIMA
2. Cancer-related information summaries from the National Cancer Institute
3. Clinical trials announcements from EudraCT

Annotations

Annotation process

• 3800 sentences: Semi-automatic alignment of technical and patient versions of medical sentences. Inter-annotator agreement measured with Cohen's Kappa (average Kappa = 0.839 +- 0.076; very high agreement).
• 1200 sentences: Manual simplification technical medical sentences, both at the syntactic and lexical level. Three independent evaluators assessed the quality of the simplification by means of a 5-point Likert scale questionnaires. Human evaluators scored the simplified sentences according to grammar/fluency (average 4.8%), semantic adequacy/meaning coherence (average 4.9%) and overall simplification (average 4.3%).

Who are the annotators?

• 3800 sentences:
  Leonardo Campillos-Llanos
  Adrián Capllonch-Carrión
  Ana Rosa Terroba-Reinares
  Ana Valverde-Mateos
  Sofía Zakhir-Puig
  

• 1200 sentences:
  Rocío Bartolomé-Rodríguez
  Leonardo Campillos-Llanos
  Ana Rosa Terroba-Reinares
  

Personal and Sensitive Information

No personal and sensitive information was used.

Licensing Information

These data are aimed at research and educational purposes, and released under a Creative Commons Non-Commercial Attribution (CC-BY-NC-A) 4.0 International License.

Citation Information

• 3800 sentences: Campillos Llanos, L., Terroba Reinares, A. R., Zakhir Puig, S., Valverde, A., & Capllonch-Carrión, A. (2022). Building a comparable corpus and a benchmark for Spanish medical text simplification. Procesamiento del lenguaje natural, 69, pp. 189--196.

@article{2022claramedcorpus,
  title={Building a comparable corpus and a benchmark for Spanish medical text simplification},
  author={Campillos-Llanos, Leonardo and Terroba Reinares, Ana R., and Zakhir Puig, Sofía, and Valverde-Mateos, Ana and Capllonch-Carri{\'o}n},
  title={Procesamiento del Lenguaje Natural},
  volume={69},
  year={2022},
  pages={189--196},
  publisher={Sociedad Espa{\~n}ola para el Procesamiento del Lenguaje Natural}
}

• 1200 sentences: Campillos-Llanos, L., Bartolomé-Rodríguez, R. & Terroba-Reinares, A. R. (2024) Enhancing the understanding of clinical trials with a sentence-level simplification dataset. Procesamiento del Lenguaje Natural, 72, pp. 31--43.

@article{campillosetal2024,
  title={Enhancing the understanding of clinical trials with a sentence-level simplification dataset},
  author={Campillos-Llanos, Leonardo and Bartolom{\'e}-Rodr{\'i}guez, Roc{\'i}o and Terroba Reinares, Ana R.},
  title={Procesamiento del Lenguaje Natural},
  volume={72},
  year={2024},
  pages={31--43},
  publisher={Sociedad Espa{\~n}ola para el Procesamiento del Lenguaje Natural}
}

Contributions

Thanks to Jónathan Heras from Universidad de La Rioja (@joheras) for formatting this dataset for Hugging Face.