README.md

metadata

dataset_info:
  - config_name: conversational
    features:
      - name: id
        dtype: string
      - name: prompt
        list:
          - name: role
            dtype: string
          - name: content
            dtype: string
      - name: completion
        list:
          - name: role
            dtype: string
          - name: content
            dtype: string
      - name: Label
        dtype: string
    splits:
      - name: train
        num_bytes: 36626198
        num_examples: 13371
      - name: test
        num_bytes: 1520013
        num_examples: 552
    download_size: 8896008
    dataset_size: 38146211
  - config_name: processed
    features:
      - name: id
        dtype: string
      - name: og_id
        dtype: string
      - name: PMID
        dtype: string
      - name: Category
        dtype: string
      - name: Instruction
        dtype: string
      - name: Context
        dtype: string
      - name: Label
        dtype: string
      - name: Spans
        sequence: string
      - name: Tagged_Spans
        list:
          - name: end_token
            dtype: int64
          - name: label_id
            dtype: int64
          - name: start_token
            dtype: int64
          - name: text
            dtype: string
    splits:
      - name: train
        num_bytes: 31213858
        num_examples: 13371
      - name: test
        num_bytes: 1309571
        num_examples: 552
    download_size: 8093947
    dataset_size: 32523429
  - config_name: source
    features:
      - name: id
        dtype: string
      - name: PMID
        dtype: string
      - name: Split
        dtype: string
      - name: Quality
        dtype: string
      - name: Abstract
        dtype: string
      - name: Tokens
        sequence: string
      - name: Participants_Labels
        sequence: int64
      - name: Interventions_Labels
        sequence: int64
      - name: Outcomes_Labels
        sequence: int64
    splits:
      - name: train
        num_bytes: 47544758
        num_examples: 4457
      - name: test
        num_bytes: 1961875
        num_examples: 184
    download_size: 7561664
    dataset_size: 49506633
configs:
  - config_name: conversational
    data_files:
      - split: train
        path: conversational/train-*
      - split: test
        path: conversational/test-*
  - config_name: processed
    data_files:
      - split: train
        path: processed/train-*
      - split: test
        path: processed/test-*
  - config_name: source
    data_files:
      - split: train
        path: source/train-*
      - split: test
        path: source/test-*
license: cc-by-sa-4.0
task_categories:
  - token-classification
language:
  - en
tags:
  - medical
pretty_name: EBM_NLP
size_categories:
  - 10K<n<100K

EBM-NLP

Dataset Description

	Links
Homepage:	Huggingface
Original Repository:	Github
Paper:	arXiv
Contact (Main Original Author):	Benjamin Nye (nye.b@husky.neu.edu)
Contact (Curator):	Artur Guimarães (artur.guimas@gmail.com)

Dataset Summary

We present a corpus of 5,000 richly annotated abstracts of medical articles describing clinical randomized controlled trials. Annotations include demarcations of text spans that describe the Patient population enrolled, the Interventions studied and to what they were Compared, and the Outcomes measured (the ‘PICO’ elements). These spans are further annotated at a more granular level, e.g., individual interventions within them are marked and mapped onto a structured medical vocabulary. We acquired annotations from a diverse set of workers with varying levels of expertise and cost. We describe our data collection process and the corpus itself in detail. We then outline a set of challenging NLP tasks that would aid searching of the medical literature and the practice of evidence-based medicine.

Data Instances

{
  'TO:DO': ...,
  ...
}

Data Fields

TO:DO

Additional Information

Dataset Curators

Original Paper

• Benjamin Nye (nye.b@husky.neu.edu) - Northeastern University
• Junyi Jessy Li (jessy@austin.utexas.edu) - UT Austin
• Roma Patel (romapatel996@gmail.com) - Rutgers University
• Yinfei Yang (yangyin7@gmail.com) - No affiliation
• Iain J. Marshall (iain.marshall@kcl.ac.uk) - King's College London
• Ani Nenkova (nenkova@seas.upenn.edu) - UPenn
• Byron C. Wallace (b.wallace@northeastern.edu) - Northeastern University

Huggingface Curator

• Artur Guimarães (artur.guimas@gmail.com) - INESC-ID / University of Lisbon - Instituto Superior Técnico

Licensing Information

CC BY-SA 4.0

Citation Information

@inproceedings{nye2018corpus,
  title={A corpus with multi-level annotations of patients, interventions and outcomes to support language processing for medical literature},
  author={Nye, Benjamin and Li, Junyi Jessy and Patel, Roma and Yang, Yinfei and Marshall, Iain and Nenkova, Ani and Wallace, Byron C},
  booktitle={Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)},
  pages={197--207},
  year={2018}
}

Contributions

Thanks to araag2 for adding this dataset.