Assessing the article screening efficiency of artificial intelligence for Systematic Reviews.

Journal: Journal of dentistry
PMID: 39067652

Abstract

OBJECTIVES: Artificial intelligence (AI) tools utilizing machine learning (ML) have gained increasing utility in medicine and academia as a means of enhancing efficiency. ASReview is one such AI program designed to streamline the systematic review process through the automated prioritization of relevant articles for screening. This study examined the screening efficiency of ASReview when conducting systematic reviews and the potential factors that could influence its efficiency.

Authors

  • Yu-Ting Chan
    Department of Periodontology, Henry M. Goldman School of Dental Medicine, Boston University, 635 Albany Street, Boston, MA 02118, United States.
  • Jilaine Elliscent Abad
    Department of Periodontology, Henry M. Goldman School of Dental Medicine, Boston University, 635 Albany Street, Boston, MA 02118, United States.
  • Serge Dibart
    Department of Periodontology and Oral Biology, Henry M. Goldman School of Dental Medicine, Boston University, Boston, Massachusetts, USA.
  • Jeremy R Kernitsky
    Department of Periodontology, Henry M. Goldman School of Dental Medicine, Boston University, 635 Albany Street, Boston, MA 02118, United States. Electronic address: jkernits@bu.edu.

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