Discriminating between empirical studies and nonempirical works using automated text classification.

Objective: Identify the most performant automated text classification method (eg, algorithm) for differentiating empirical studies from nonempirical works in order to facilitate systematic mixed studies reviews.

Methods: The algorithms were trained and validated with 8050 database records, which had previously been manually categorized as empirical or nonempirical. A Boolean mixed filter developed for filtering MEDLINE records (title, abstract, keywords, and full texts) was used as a baseline.