Datasets:
ohsumed

	---
	pretty_name: Ohsumed
	annotations_creators:
	- expert-generated
	language_creators:
	- crowdsourced
	language:
	- en
	license:
	- cc-by-nc-4.0
	multilinguality:
	- monolingual
	size_categories:
	- 100K<n<1M
	source_datasets:
	- original
	task_categories:
	- text-classification
	task_ids:
	- multi-label-classification
	paperswithcode_id: null
	dataset_info:
	features:
	- name: seq_id
	dtype: int64
	- name: medline_ui
	dtype: int64
	- name: mesh_terms
	dtype: string
	- name: title
	dtype: string
	- name: publication_type
	dtype: string
	- name: abstract
	dtype: string
	- name: author
	dtype: string
	- name: source
	dtype: string
	config_name: ohsumed
	splits:
	- name: train
	num_bytes: 60117860
	num_examples: 54709
	- name: test
	num_bytes: 338533901
	num_examples: 293855
	download_size: 139454017
	dataset_size: 398651761
	---

	# Dataset Card for ohsumed

	## Table of Contents
	- [Dataset Description](#dataset-description)
	- [Dataset Summary](#dataset-summary)
	- [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
	- [Languages](#languages)
	- [Dataset Structure](#dataset-structure)
	- [Data Instances](#data-instances)
	- [Data Fields](#data-fields)
	- [Data Splits](#data-splits)
	- [Dataset Creation](#dataset-creation)
	- [Curation Rationale](#curation-rationale)
	- [Source Data](#source-data)
	- [Annotations](#annotations)
	- [Personal and Sensitive Information](#personal-and-sensitive-information)
	- [Considerations for Using the Data](#considerations-for-using-the-data)
	- [Social Impact of Dataset](#social-impact-of-dataset)
	- [Discussion of Biases](#discussion-of-biases)
	- [Other Known Limitations](#other-known-limitations)
	- [Additional Information](#additional-information)
	- [Dataset Curators](#dataset-curators)
	- [Licensing Information](#licensing-information)
	- [Citation Information](#citation-information)
	- [Contributions](#contributions)

	## Dataset Description

	- Homepage: http://davis.wpi.edu/xmdv/datasets/ohsumed.html
	- Repository: https://trec.nist.gov/data/filtering/t9.filtering.tar.gz
	- Paper: https://link.springer.com/chapter/10.1007/978-1-4471-2099-5_20
	- Leaderboard:
	- Point of Contact: [William Hersh](mailto:hersh@OHSU.EDU) [Aakash Gupta](mailto:aakashg80@gmail.com)

	### Dataset Summary

	The OHSUMED test collection is a set of 348,566 references from
	MEDLINE, the on-line medical information database, consisting of
	titles and/or abstracts from 270 medical journals over a five-year
	period (1987-1991). The available fields are title, abstract, MeSH
	indexing terms, author, source, and publication type. The National
	Library of Medicine has agreed to make the MEDLINE references in the
	test database available for experimentation, restricted to the
	following conditions:

	1. The data will not be used in any non-experimental clinical,
	library, or other setting.
	2. Any human users of the data will explicitly be told that the data
	is incomplete and out-of-date.

	Please check this [readme](https://trec.nist.gov/data/filtering/README.t9.filtering) for more details


	### Supported Tasks and Leaderboards

	[Text Classification](https://paperswithcode.com/sota/text-classification-on-ohsumed)

	### Languages

	The text is primarily in English. The BCP 47 code is `en`

	## Dataset Structure

	### Data Instances

	```
	{'seq_id': 7770,
	'medline_ui': 87120420,
	'mesh_terms': 'Adult; Aged; Aneurysm/CO; Arteriovenous Fistula/TH; Carotid Arteries; Case Report; Female; Human; Jugular Veins; Male; Methods; Middle Age; Neck/BS; Vertebral Artery.',
	'title': 'Arteriovenous fistulas of the large vessels of the neck: nonsurgical percutaneous occlusion.',
	'publication_type': 'JOURNAL ARTICLE.',
	'abstract': 'We describe the nonsurgical treatment of arteriovenous fistulas of the large vessels in the neck using three different means of endovascular occlusion of these large lesions, which are surgically difficult to approach and treat.',
	'author': 'Vitek JJ; Keller FS.',
	'source': 'South Med J 8705; 80(2):196-200'}

	```


	### Data Fields

	Here are the field definitions:

	- seg_id: sequential identifier
	(important note: documents should be processed in this order)
	- medline_ui: MEDLINE identifier (UI)
	(<DOCNO> used for relevance judgements)
	- mesh_terms: Human-assigned MeSH terms (MH)
	- title: Title (TI)
	- publication_type : Publication type (PT)
	- abstract: Abstract (AB)
	- author: Author (AU)
	- source: Source (SO)

	Note: some abstracts are truncated at 250 words and some references
	have no abstracts at all (titles only). We do not have access to the
	full text of the documents.

	### Data Splits

	The files are Train/ Test. Where the training has files from 1987 while the test files has abstracts from 1988-91

	Total number of files:
	Train: 54710
	Test: 348567


	## Dataset Creation

	### Curation Rationale

	The OHSUMED document collection was obtained by William Hersh
	(hersh@OHSU.EDU) and colleagues for the experiments described in the
	papers below. [Check citation](#citation-information)

	### Source Data

	#### Initial Data Collection and Normalization

	[More Information Needed]

	#### Who are the source language producers?

	The test collection was built as part of a study assessing the use of
	MEDLINE by physicians in a clinical setting (Hersh and Hickam, above).
	Novice physicians using MEDLINE generated 106 queries. Only a subset
	of these queries were used in the TREC-9 Filtering Track. Before
	they searched, they were asked to provide a statement of information
	about their patient as well as their information need.
	The data was collected by William Hersh & colleagues

	### Annotations

	#### Annotation process

	The existing OHSUMED topics describe actual information needs, but the
	relevance judgements probably do not have the same coverage provided
	by the TREC pooling process. The MeSH terms do not directly represent
	information needs, rather they are controlled indexing terms. However,
	the assessment should be more or less complete and there are a lot of
	them, so this provides an unusual opportunity to work with a very
	large topic sample.

	The topic statements are provided in the standard TREC format

	#### Who are the annotators?

	Each query was replicated by four searchers, two physicians
	experienced in searching and two medical librarians. The results were
	assessed for relevance by a different group of physicians, using a
	three point scale: definitely, possibly, or not relevant. The list of
	documents explicitly judged to be not relevant is not provided here.
	Over 10% of the query-document pairs were judged in duplicate to
	assess inter-observer reliability. For evaluation, all documents
	judged here as either possibly or definitely relevant were
	considered relevant. TREC-9 systems were allowed to distinguish
	between these two categories during the learning process if desired.

	### Personal and Sensitive Information

	No PII data is present in the train, test or query files.

	## Considerations for Using the Data

	### Social Impact of Dataset

	[More Information Needed]

	### Discussion of Biases

	[More Information Needed]

	### Other Known Limitations

	Dataset provided for research purposes only. Please check dataset license for additional information.

	## Additional Information

	### Dataset Curators

	[Aakash Gupta](mailto:aakashg80@gmail.com)
	Th!nkEvolve Consulting and Researcher at CoronaWhy

	### Licensing Information

	CC BY-NC 4.0

	### Citation Information

	Hersh WR, Buckley C, Leone TJ, Hickam DH, OHSUMED: An interactive
	retrieval evaluation and new large test collection for research,
	Proceedings of the 17th Annual ACM SIGIR Conference, 1994, 192-201.

	Hersh WR, Hickam DH, Use of a multi-application computer workstation
	in a clinical setting, Bulletin of the Medical Library Association,
	1994, 82: 382-389.

	### Contributions

	Thanks to [@skyprince999](https://github.com/skyprince999) for adding this dataset.