Literature-based discovery approaches for evidence-based healthcare: a systematic review.
Literature-based discovery approaches for evidence-based healthcare: a systematic review.
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DOI：
10.1007/s12553-021-00605-y
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发表时间：
2021
影响因子：
2.5
通讯作者：
Khedo KK
中科院分区：
文献类型：
--
作者：
Cheerkoot-Jalim S;Khedo KK
基于文献的发现（LBD）是一种文本挖掘技术，用于通过识别来自不同来源的概念之间的联系，从大量文献来源中生成新的假设。它主要应用的主要领域之一是医疗保健领域，因此有希望的结果，以新的假设的形式，已被报道。这项工作的目的是对医疗保健领域最近发表的关于LBD的文献进行系统的综述，以评估所使用方法的趋势，并确定此类系统的问题和挑战。审查是按照基钦纳姆方法的原则进行的。已对选定的研究进行了仔细审查，并根据PRISMA指南报告了得出的结果。综述结果揭示了有关应用领域、考虑的数据源、使用的方法、准确性和可靠性方面的性能以及未来研究挑战的有用信息。本综述的结果将有利于LBD研究人员和医疗保健领域的其他利益相关者，为他们提供关于采用的方法、考虑的数据源、使用的评估模型和需要反思的挑战的有用见解。这项工作的综合结果揭示了推动新的LBD模型的最新问题和挑战，并为它们在医疗保健领域的其他不同领域的应用提供了途径。据我们所知，最近还没有进行过这样的审查。
Literature-Based Discovery (LBD) is a text mining technique used to generate novel hypotheses from vast amounts of literature sources, by identifying links between concepts from disparate sources. One of the main areas where it has been predominantly applied is the healthcare domain, whereby promising results, in the form of novel hypotheses, have been reported. The purpose of this work was to conduct a systematic literature review of recent publications on LBD in the healthcare domain in order to assess the trends in the approaches used and to identify issues and challenges for such systems. The review was conducted following the principles of the Kitchenham method. The selected studies have been scrutinized and the derived findings have been reported following the PRISMA guidelines. The review results reveal useful information regarding the application areas, the data sources considered, the approaches used, the performance in terms of accuracy and reliability and future research challenges. The results of this review will be beneficial to LBD researchers and other stakeholders in the healthcare domain, by providing them with useful insights on the approaches to adopt, data sources to consider, evaluation model to use and challenges to reflect on. The synthesis of the results of this work has shed light on recent issues and challenges that drive new LBD models and provides avenues for their application in other diverse areas in the healthcare domain. To the best of our knowledge, no such recent review has been conducted.
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影响因子：
5.2
作者：
Blair, Mitch
通讯作者：
Blair, Mitch
影响因子：
15.8
作者：
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Meier, John J.;Conkling, Thomas W.
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Rindflesch, Thomas C.
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通讯作者：
Grant J