Screening nonrandomized studies for medical systematic reviews: a comparative study of classifiers.
Objectives: To investigate whether (1) machine learning classifiers can help identify nonrandomized studies eligible for full-text screening by systematic reviewers; (2) classifier performance varies with optimization; and (3) the number of citations to screen can be reduced.Methods: We used an open...
| Publicado en: | Artificial Intelligence in Medicine Vol. 55; no. 3; pp. 197 - 208 |
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| Autores principales: | , , , |
| Formato: | research Journal Article |
| Publicado: |
Elsevier B.V.
2012 Jul
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| Acceso en línea: | Ver este registro en EBSCOhost |