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Table 6 Semi-automation test with RobotAnalyst using a training set of dually reviewed citations from a review-of-review and randomly selected citations with labels from full-text screening

From: Comparison of a traditional systematic review approach with review-of-reviews and semi-automation as strategies to update the evidence

 

Traditional search

Total citations: 3181

Title-abstract screening: 201 includes/2980 excludes

Full-text screening: 59 includes/3122 excludes

 

Training set: ROR citations + 30% random citations

Labeled citations: 1063 (33%)

Training set labels: TP (40), FP (0), TN (1023)

Unlabeled citations assigned inclusion prediction by ML algorithm: 2118

Inclusion prediction: 0.3

Inclusion prediction: 0.4

Inclusion prediction: 0.5

Predicted includes

2094

1765

676

Predicted excludes

24

353

1442

Sensitivity

98%

84%

80%

Specificity

34%

44%

79%

Missed citations

1

3

12

Burden

99%

89%

55%

Time savings (min)

12

177

721

  1. FP false positive, ML machine learning, TP true positive, TN true positive