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

Yu-Ting Chan1, Jilaine Elliscent Abad1, Serge Dibart1

  • 1Department of Periodontology, Henry M. Goldman School of Dental Medicine, Boston University, 635 Albany Street, Boston, MA 02118, United States.

Journal of Dentistry
|July 27, 2024
PubMed
Summary
This summary is machine-generated.

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Artificial intelligence (AI) tools like ASReview significantly improve systematic review efficiency by prioritizing articles. This AI program can save approximately 60% of the time and effort typically needed for article screening.

Area of Science:

  • Medical informatics
  • Artificial intelligence in healthcare
  • Systematic review methodology

Background:

  • Machine learning (ML) and AI tools enhance efficiency in medicine and academia.
  • ASReview is an AI program designed to streamline systematic reviews by automating article prioritization.
  • This study evaluates ASReview's screening efficiency and influencing factors.

Purpose of the Study:

  • To examine the screening efficiency of ASReview in systematic reviews.
  • To identify factors influencing ASReview's efficiency.

Main Methods:

  • Searched six periodontics topics in PubMed and Web of Science.
  • Trained ASReview with relevant/irrelevant articles for ML optimization.
  • Evaluated screening efficiency based on normalized non-reviewed articles and time expenditure.
Keywords:
ASReviewArtificial intelligenceEfficiencySystematic review

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Main Results:

  • An average of 60.2% of articles did not require extensive screening.
  • All relevant articles were identified within the first 39.8% of reviewed publications.
  • No significant efficiency variations were found with different training methods or article ratios.

Conclusions:

  • ASReview provides an average 60.2% improvement in screening efficiency due to ML capabilities.
  • Human discernment remains crucial for training AI tools like ASReview effectively.
  • ASReview has the potential to save approximately 60% of time and effort in article screening.