Measuring the impact of screening automation on meta-analyses of diagnostic test accuracy.

ABSTRACT:

Background

The large and increasing number of new studies published each year is making literature identification in systematic reviews ever more time-consuming and costly. Technological assistance has been suggested as an alternative to the conventional, manual study identification to mitigate the cost, but previous literature has mainly evaluated methods in terms of recall (search sensitivity) and workload reduction. There is a need to also evaluate whether screening prioritization methods leads to the same results and conclusions as exhaustive manual screening. In this study, we examined the impact of one screening prioritization method based on active learning on sensitivity and specificity estimates in systematic reviews of diagnostic test accuracy.

Methods

We simulated

SUBMITTER: Norman CR 

PROVIDER: S-EPMC6819363 | biostudies-literature | 2019 Oct

REPOSITORIES: biostudies-literature