从行为科学随机对照试验中提取和预测知识：以戒烟为例。
Knowledge Extraction and Prediction from Behavior Science Randomized Controlled Trials: A Case Study in Smoking Cessation.
机构信息
IBM Research Europe, Dublin, Ireland.
University College London, UK.
出版信息
AMIA Annu Symp Proc. 2021 Jan 25;2020:253-262. eCollection 2020.
Abstract
Due to the fast pace at which randomized controlled trials are published in the health domain, researchers, consultants and policymakers would benefit from more automatic ways to process them by both extracting relevant information and automating the meta-analysis processes. In this paper, we present a novel methodology based on natural language processing and reasoning models to 1) extract relevant information from RCTs and 2) predict potential outcome values on novel scenarios, given the extracted knowledge, in the domain of behavior change for smoking cessation.
摘要
由于健康领域随机对照试验的发布速度很快，研究人员、顾问和政策制定者将受益于通过提取相关信息和自动化荟萃分析过程来更自动地处理这些试验的方法。在本文中，我们提出了一种基于自然语言处理和推理模型的新方法，用于 1）从 RCT 中提取相关信息，以及 2）根据提取的知识，在戒烟行为改变领域，对新场景下的潜在结果值进行预测。
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