Use of Text-mining and Machine Learning Approaches to Conduct a Rapid Literature Survey on Environmental Chemicals and the Thyroid

This data set contains supplemental SWIFT-Review file for the article "Use of Text-mining and Machine Learning Approaches to Conduct a Rapid Literature Survey on Environmental Chemicals and the Thyroid" (Kiros et al., EI 2017)

SWIFT-Review_Thyroid Literature Database.stp contains:
235,960 records identified in PubMed with ability to filter records by type of evidence: publication type, chemicals studied, evidence streams (human, animal, in vitro) and thyroid endpoints/outcomes. This file can be opened and explored after installing SWIFT-Review software https://swift.sciome.com/SWIFTupdates/Tutorial/Installation Instructions.pdf. The software is available for free download at (http://www.sciome.com/swift-review/)

本数据集包含针对文章《利用文本挖掘与机器学习方法快速调研环境化学物质与甲状腺》的补充SWIFT-Review文件（Kiros等，EI 2017）。SWIFT-Review_Thyroid文献数据库.stp文件中包含：在PubMed上识别出的235,960条记录，具备按证据类型、出版物类型、研究化学物质、证据流（人类、动物、体外）以及甲状腺终点/结果进行筛选的能力。安装SWIFT-Review软件后，可打开并探索此文件，软件免费下载地址为（http://www.sciome.com/swift-review/）。