llangnickel/long-covid-classification-data

该数据集包含与长COVID相关的PubMed文章摘要，这些文章由信息专家手动收集。数据集分为训练集、开发集和测试集，其中正例和负例的数量分别为：训练集215正例和199负例，开发集76正例和62负例，测试集70正例和68负例，总计690篇文章。

This dataset comprises PubMed article abstracts associated with long COVID, which were manually curated by information specialists. The dataset is split into training, development, and test sets, with the counts of positive and negative samples as follows: the training set contains 215 positive and 199 negative samples, the development set has 76 positive and 62 negative samples, and the test set includes 70 positive and 68 negative samples, resulting in a total of 690 articles across all splits.

原始信息汇总

数据集概述

基本信息

• 名称: 包含PubMed摘要的数据集，涉及长COVID或非长COVID相关内容。
• 语言: 英语（en）
• 许可证: CC-BY-4.0
• 多语言性: 单语（monolingual）
• 数据来源: 原始数据
• 任务类别: 文本分类

数据描述

• 长COVID相关文章由信息专家手动收集。

数据集大小

类别	训练集	开发集	测试集	总计
阳性例子	215	76	70	345
阴性例子	199	62	68	345
总计	414	238	138	690

引用信息

@article{10.1093/database/baac048, author = {Langnickel, Lisa and Darms, Johannes and Heldt, Katharina and Ducks, Denise and Fluck, Juliane}, title = "{Continuous development of the semantic search engine preVIEW: from COVID-19 to long COVID}", journal = {Database}, volume = {2022}, year = {2022}, month = {07}, issn = {1758-0463}, doi = {10.1093/database/baac048}, url = {https://doi.org/10.1093/database/baac048}, note = {baac048}, eprint = {https://academic.oup.com/database/article-pdf/doi/10.1093/database/baac048/44371817/baac048.pdf}, }