Development and Validation of a Literature Screening Tool: Few-Shot Learning Approach in Systematic Reviews.

Journal: Journal of medical Internet research
PMID: 39662894

Abstract

BACKGROUND: Systematic reviews (SRs) are considered the highest level of evidence, but their rigorous literature screening process can be time-consuming and resource-intensive. This is particularly challenging given the rapid pace of medical advancements, which can quickly make SRs outdated. Few-shot learning (FSL), a machine learning approach that learns effectively from limited data, offers a potential solution to streamline this process. Sentence-bidirectional encoder representations from transformers (S-BERT) are particularly promising for identifying relevant studies with fewer examples.

Authors

  • Phongphat Wiwatthanasetthakarn
    Department of Clinical Epidemiology and Biostatistics, Faculty of Medicine Ramathibodi Hospital, Mahidol University, Bangkok, Thailand.
  • Wanchana Ponthongmak
    Department of Clinical Epidemiology and Biostatistics, Faculty of Medicine Ramathibodi Hospital, Mahidol University, Bangkok, Thailand.
  • Panu Looareesuwan
    Department of Clinical Epidemiology and Biostatistics, Faculty of Medicine Ramathibodi Hospital, Mahidol University, Bangkok, Thailand.
  • Amarit Tansawet
    Department of Surgery, Faculty of Medicine Vajira Hospital, Navamindradhiraj University, Bangkok, Thailand. Electronic address: amarit@nmu.ac.th.
  • Pawin Numthavaj
    Department of Clinical Epidemiology and Biostatistics, Faculty of Medicine Ramathibodi Hospital, Mahidol University, Bangkok, Thailand.
  • Gareth J McKay
    Center for Public Health, Royal Victoria Hospital, Queen's University Belfast, Belfast, UK.
  • John Attia
    School of Medicine and Public Health, University of Newcastle, Callaghan, NSW, Australia.
  • Ammarin Thakkinstian
    Departments of Clinical Epidemiology and Biostatistics; and.

Keywords

External Resources

Popular Topics
Recent Journals