The state of artificial intelligence in medical research: A survey of corresponding authors from top medical journals.

Journal: PloS one
Published Date:

Abstract

Natural Language Processing (NLP) is a subset of artificial intelligence that enables machines to understand and respond to human language through Large Language Models (LLMs)‥ These models have diverse applications in fields such as medical research, scientific writing, and publishing, but concerns such as hallucination, ethical issues, bias, and cybersecurity need to be addressed. To understand the scientific community's understanding and perspective on the role of Artificial Intelligence (AI) in research and authorship, a survey was designed for corresponding authors in top medical journals. An online survey was conducted from July 13th, 2023, to September 1st, 2023, using the SurveyMonkey web instrument, and the population of interest were corresponding authors who published in 2022 in the 15 highest-impact medical journals, as ranked by the Journal Citation Report. The survey link has been sent to all the identified corresponding authors by mail. A total of 266 authors answered, and 236 entered the final analysis. Most of the researchers (40.6%) reported having moderate familiarity with artificial intelligence, while a minority (4.4%) had no associated knowledge. Furthermore, the vast majority (79.0%) believe that artificial intelligence will play a major role in the future of research. Of note, no correlation between academic metrics and artificial intelligence knowledge or confidence was found. The results indicate that although researchers have varying degrees of familiarity with artificial intelligence, its use in scientific research is still in its early phases. Despite lacking formal AI training, many scholars publishing in high-impact journals have started integrating such technologies into their projects, including rephrasing, translation, and proofreading tasks. Efforts should focus on providing training for their effective use, establishing guidelines by journal editors, and creating software applications that bundle multiple integrated tools into a single platform.

Authors

  • Michele Salvagno
    Department of Intensive Care, Erasme Hospital, Université Libre de Bruxelles, 1070, Brussels, Belgium. michele.salvagno@ulb.be.
  • Alessandro De Cassai
    Sant'Antonio Anesthesia and Intensive Care Unit, University Hospital of Padua, Padua, Italy.
  • Stefano Zorzi
    Department of Intensive Care, Hôpital Universitaire de Bruxelles (HUB), Brussels, Belgium.
  • Mario Zaccarelli
    Department of Intensive Care, Hôpital Universitaire de Bruxelles (HUB), Brussels, Belgium.
  • Marco Pasetto
    Department of Intensive Care, Hôpital Universitaire de Bruxelles (HUB), Brussels, Belgium.
  • Elda Diletta Sterchele
    Department of Intensive Care, Hôpital Universitaire de Bruxelles (HUB), Brussels, Belgium.
  • Dmytro Chumachenko
    Mathematical Modelling and Artificial Intelligence Department, National Aerospace University Kharkiv Aviation Institute, 61072 Kharkiv, Ukraine.
  • Alberto Giovanni Gerli
    Department of Clinical Sciences and Community Health, Università Degli Studi di Milano, 20122, Milan, Italy.
  • Razvan Azamfirei
    Department of Anesthesiology and Critical Care Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA. razvan@jhmi.edu.
  • Fabio Silvio Taccone
    Department of Intensive Care, Erasme Hospital, Université Libre de Bruxelles, 1070, Brussels, Belgium.