Exploring the potential of ChatGPT in the peer review process: An observational study.

Journal: Diabetes & metabolic syndrome
PMID: 38330745

Abstract

BACKGROUND: Peer review is the established method for evaluating the quality and validity of research manuscripts in scholarly publishing. However, scientific peer review faces challenges as the volume of submitted research has steadily increased in recent years. Time constraints and peer review quality assurance can place burdens on reviewers, potentially discouraging their participation. Some artificial intelligence (AI) tools might assist in relieving these pressures. This study explores the efficiency and effectiveness of one of the artificial intelligence (AI) chatbots, ChatGPT (Generative Pre-trained Transformer), in the peer review process.

Authors

  • Ahmed Saad
    Biochemistry Department, Faculty of Agriculture, Zagazig University, Zagazig 44511, Egypt.
  • Nathan Jenko
    Department of Musculoskeletal Radiology, The Royal Orthopaedic Hospital NHS Foundation Trust, Northfield, Birmingham, UK (S.A., N.J., A.M.D., R.B.).
  • Sisith Ariyaratne
    Department of Musculoskeletal Radiology, The Royal Orthopedic Hospital, Bristol Road South, Northfield, Birmingham, UK.
  • Nick Birch
    Bragborough Hall Health and Wellness Centre, Daventry, UK.
  • Karthikeyan P Iyengar
    Department of Orthopedics, Southport and Ormskirk Hospital, Southport, UK.
  • Arthur Mark Davies
    Department of Musculoskeletal Radiology, Royal Orthopaedic Hospital, Birmingham, B31 2AP, UK. Electronic address: mark.davies8@nhs.net.
  • Raju Vaishya
    Department of Orthopaedics, Indraprastha Apollo Hospital, SaritaVihar, Mathura Road, 110076, New Delhi, India. Electronic address: raju.vaishya@gmail.com.
  • Rajesh Botchu
    Department of Radiology, Royal Orthopedic Hospital, Birmingham, UK.

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