---
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](https://github.com/bepnye/EBM-NLP)  |
| **Original Repository:**        |  [Github](https://github.com/bepnye/EBM-NLP)  |
| **Paper:**                      |  [arXiv](https://arxiv.org/abs/1806.04185)  |
| **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](https://araag2.netlify.app/) (artur.guimas@gmail.com) - INESC-ID / University of Lisbon - Instituto Superior Técnico

### Licensing Information

[CC BY-SA 4.0](https://creativecommons.org/licenses/by-sa/4.0/deed.en)

### Citation Information

```bibtex
@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](https://github.com/araag2) for adding this dataset.