Automating Biomedical Evidence Synthesis: RobotReviewer

被引：57

作者：

Marshall, Iain J. ^{[1
]}

Kuiper, Joel ^{[2
]}

Banner, Edward ^{[3
]}

Wallace, Byron C. ^{[3
]}

机构：

[1] Kings Coll London, Dept Primary Care & Publ Hlth Sci, London, England

[2] Northeastern Univ, Evidence, Boston, MA 02115 USA

[3] Northeastern Univ, Coll Comp & Informat Sci, Boston, MA 02115 USA

来源：

PROCEEDINGS OF THE 55TH ANNUAL MEETING OF THE ASSOCIATION FOR COMPUTATIONAL LINGUISTICS (ACL 2017): SYSTEM DEMONSTRATIONS | 2017年

基金：

英国医学研究理事会; 美国国家卫生研究院;

关键词：

BIAS;

D O I：

10.18653/v1/P17-4002

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

We present RobotReviewer, an open-source web-based system that uses machine learning and NLP to semi-automate biomedical evidence synthesis, to aid the practice of Evidence-Based Medicine. RobotReviewer processes full-text journal articles (PDFs) describing randomized controlled trials (RCTs). It appraises the reliability of RCTs and extracts text describing key trial characteristics (e.g., descriptions of the population) using novel NLP methods. RobotReviewer then automatically generates a report synthesising this information. Our goal is for RobotReviewer to automatically extract and synthesise the full-range of structured data needed to inform evidence-based practice.

引用

页码：7 / 12

页数：6

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