ObjectivesMachine learning systems can considerably reduce the time and effort needed by experts to perform new systematic reviews (SRs). This study investigates categorization models, which are trained on a combination of included and commonly excluded articles, which can improve performance by identifying high quality articles for new procedures or drug SRs.
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