Datasets:
Tasks:
Token Classification
Modalities:
Text
Formats:
parquet
Languages:
English
Size:
10K - 100K
ArXiv:
Tags:
medical
License:
| 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. |