Data Extraction and Synthesis in Systematic Reviews of Diagnostic Test Accuracy: A Corpus for Automating and Evaluating the Process.

ABSTRACT: BACKGROUND:Systematic reviews are critical for obtaining accurate estimates of diagnostic test accuracy, yet these require extracting information buried in free text articles, an often laborious process. OBJECTIVE:We create a dataset describing the data extraction and synthesis processes in 63 DTA systematic reviews, and demonstrate its utility by using it to replicate the data synthesis in the original reviews. METHOD:We construct our dataset using a custom automated extraction pipeline complemented with manual extraction, verification, and post-editing. We evaluate using manual assessment by two annotators and by comparing against data extracted from source files. RESULTS:The constructed dataset contains 5,848 test results for 1,354 diagnostic tests from 1,738 diagnostic studies. We obse

SUBMITTER: Norman C 

PROVIDER: S-EPMC6371350 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature