Priority Screening Algorithm

This tool's purpose is to prioritise the scientific papers that could possibley include the content that users are looking for during the screening phase of systematic review. The model is actively trained based on the manual screening decisions of the systematic reviewer. It 'learns' to apply a label and then labels 'unseen' records. With this information it then ranks (and re-ranks) records that are being screened in systematic reviews. Applying this model on the 'unseen'/unreviewed scientific papers, has the...

The decision made by the tool does not directly affect the public. It's used to improve the efficiency of our processes. All approaches to screening are accompanied by a 10% Quality Assurance check which involves another reviewer blind screening 10% of the studies and then a comparison is made of the screening decisions. Any discrepancies are disucssed to agree whether the study should be included or excluded with...

Title and Abstract of scientific publications are the 'predictors', and the screening decisions made by the reviewer is the 'target' variables for logistic regression algorithm.