Automatic Summarization of Results from Clinical Trials

Rodney L. Summerscales, S. Argamon, Shangda Bai, J. Hupert, A. Schwartz
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引用次数: 56

Abstract

A central concern in Evidence Based Medicine (EBM) is how to convey research results effectively to practitioners. One important idea is to summarize results by key summary statistics that describe the effectiveness (or lack thereof) of a given intervention, specifically the absolute risk reduction (ARR) and number needed to treat (NNT). Manual summarization is slow and expensive, thus, with the exponential growth of the biomedical research literature, automated solutions are needed. In this paper, we present a novel method for automatically creating EBM-oriented summaries from research abstracts of randomly-controlled trials (RCTs). The system extracts descriptions of the treatment groups and outcomes, as well as various associated quantities, and then calculates summary statistics. Results on a hand-annotated corpus of research abstracts show promising, and potentially useful, results.
临床试验结果的自动摘要
循证医学(EBM)的一个中心问题是如何有效地将研究结果传达给从业者。一个重要的想法是通过描述特定干预措施有效性(或缺乏有效性)的关键汇总统计数据来总结结果,特别是绝对风险降低(ARR)和需要治疗的数量(NNT)。人工总结是缓慢和昂贵的,因此,随着生物医学研究文献的指数增长,需要自动化的解决方案。在本文中,我们提出了一种从随机对照试验(RCTs)的研究摘要中自动创建面向ebm的摘要的新方法。系统提取治疗组和结果的描述,以及各种相关数量,然后计算汇总统计。对手工注释的研究摘要语料库的结果显示出有希望的和潜在有用的结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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