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Closes #854 (#855)
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* Paragraph-level Simplification of Medical Texts ("MedParaSimp")

* remove bigbiohub.py

* Remove random text

* Updates

* update

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* Fix minor issues by maintainer

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Co-authored-by: Florian Borchert <[email protected]>
Co-authored-by: Mario Sänger <[email protected]>
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55 changes: 55 additions & 0 deletions bigbio/hub/hub_repos/medparasimp/README.md
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---
language:
- en
bigbio_language:
- English
license: apache-2.0
bigbio_license_shortname: APACHE_2p0
multilinguality: monolingual
pretty_name: Paragraph-level Simplification of Medical Texts
homepage: https://github.com/AshOlogn/Paragraph-level-Simplification-of-Medical-Texts
bigbio_pubmed: false
bigbio_public: true
bigbio_tasks:
- SUM
paperswithcode_id: paragraph-level-simplification-of-medical
---


# Dataset Card for Paragraph-level Simplification of Medical Texts

## Dataset Description

- **Homepage:** https://github.com/AshOlogn/Paragraph-level-Simplification-of-Medical-Texts
- **Pubmed:** False
- **Public:** True
- **Tasks:** SUM


This dataset is designed for the summarization NLP task. It is a
collection of technical abstracts of biomedical systematic reviews
and corresponding plain-language summaries (PLS) from the Cochrane
Database of Systematic Reviews, which comprises thousands of evidence
synopses (where authors provide an overview of all published evidence
relevant to a particular clinical question or topic). The PLS are
written by review authors; Cochrane’s PLS standards recommend that
“the PLS should be written in plain English which can be understood by
most readers without a university education”. PLS are not parallel with
every sentence in the abstract; on the contrary, they are structured heterogeneously.


## Citation Information

```
@inproceedings{devaraj-etal-2021-paragraph,
title = "Paragraph-level Simplification of Medical Texts",
author = "Devaraj, Ashwin and Marshall, Iain and Wallace, Byron and Li, Junyi Jessy",
booktitle = {Proceedings of the 2021 Conference of the North
American Chapter of the Association for Computational Linguistics},
month = jun,
year = "2021",
publisher = "Association for Computational Linguistics",
url = "https://www.aclweb.org/anthology/2021.naacl-main.395",
pages = "4972--4984",
}
```
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