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Artificial intelligence supports literature screening in medical guideline development: towards up-to-date medical guidelines.

descriptionPublicationkeyboard_double_arrow_right Preprint , Research , Other literature type 25 Jun 2021 Netherlands English Publisher:Zenodo

Authors: Harmsen, Wouter; de Groot, Janke; Harkema, Albert; van Dusseldorp, Ingeborg; De Bruin, Jonathan; Van den Brand, Sofie; Van de Schoot, Rens;

doi: 10.5281/zenodo.5031906 , 10.5281/zenodo.5031907

Artificial intelligence supports literature screening in medical guideline development: towards up-to-date medical guidelines.

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Abstract

In a time of exponential growth of new evidence supporting clinical decision making, combined with a labor-intensive process of selecting this evidence, there is a need for methods to speed up current processes in order to keep medical guidelines up-to-date. The purpose of this study was to evaluate the performance and feasibility of active learning to support the selection of relevant publications within the context of medical guideline development.

Country

Netherlands

Related Organizations

Utrecht University
Netherlands
University Museum Utrecht
Netherlands

Keywords

machine learning, active learning, systematic reviewing, medical guidelines, text data, natural language processing, guideline development

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	citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).	5
	popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.	Top 10%
	influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).	Average
	impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.	Top 10%