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

dc.contributor.authorSalvango, Michele
dc.contributor.authorDe Cassai, Alessandro
dc.contributor.authorZorzi, Stefano
dc.contributor.authorZaccarelli, Mario
dc.contributor.authorPasetto, Marco
dc.contributor.authorSterchele, Elda Diletta
dc.contributor.authorChumachenko, Dmytro
dc.contributor.authorGerli, Alberto Giovanni
dc.contributor.authorAzamfirei, Razvan
dc.contributor.authorTaccone, Fabio Silvio
dc.date.accessioned2025-08-14T16:18:23Z
dc.date.available2025-08-14T16:18:23Z
dc.date.issued2024
dc.description© 2024 Salvagno et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
dc.description.abstractNatural 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.
dc.identifier.urihttps://doi.org/10.1371/journal.pone.0309208
dc.identifier.urihttps://hdl.handle.net/10012/22160
dc.language.isoen
dc.publisherPublic Library of Science (PLOS)
dc.relation.ispartofseriesPLOS One; 19(8); e0309208
dc.rightsAttribution 4.0 Internationalen
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.subjectartificial intelligence
dc.subjectmedical journals
dc.subjectsurveys
dc.subjectlanguage
dc.subjectresearch ethics
dc.subjectsurvey research
dc.subjectnatural language processing
dc.subjectscientific publishing
dc.titleThe state of artificial intelligence in medical research: A survey of corresponding authors from top medical journals
dc.typeArticle
dcterms.bibliographicCitationSalvagno, M., Cassai, A. D., Zorzi, S., Zaccarelli, M., Pasetto, M., Sterchele, E. D., Chumachenko, D., Gerli, A. G., Azamfirei, R., & Taccone, F. S. (2024). The state of Artificial Intelligence in medical research: A survey of corresponding authors from top medical journals. PLOS ONE, 19(8). https://doi.org/10.1371/journal.pone.0309208
uws.contributor.affiliation1Faculty of Health
uws.contributor.affiliation2School of Public Health Sciences
uws.peerReviewStatusReviewed
uws.scholarLevelFaculty
uws.typeOfResourceTexten

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