Objective: To assess the ability of humans to differentiate human-authored vs artificial intelligence (AI)-generated medical manuscripts.
Methods: This is a prospective randomized survey study from October 1, 2023, to December 1, 2023, from a single academic center. Artificial intelligence-generated medical manuscripts were created using ChatGPT 3.5 and were evaluated alongside randomly selected human-authored manuscripts. Participants, who were blinded from manuscript selection and creation, were randomized to receive three manuscripts that were either human-authored or AI-generated and had to fill out a survey questionnaire after review regarding who authored the manuscript. The primary outcome was accuracy of human reviewers in differentiating manuscript authors. Secondary outcomes were to identify factors that influenced prediction accuracy.
Results: Fifty-one physicians were included in the study, including 12 post-doctorates, 19 assistant professors, and 20 associate or full professors. The overall specificity of 55.6% (95% CI, 30.8% to 78.5%), sensitivity of 31.2% (95% CI,11.0% to 58.7%), positive predictive value of 38.5% (95% CI,13.9% to 68.4%) and negative predictive value of 47.6% (95% CI, 25.7% to 70.2%). A stratified analysis of human-authored manuscripts indicated that high-impact factor manuscripts were identified with higher accuracy than low-impact factor ones (P=.037). For individual-level data, neither academic rank nor prior manuscript review experience significantly predicted the accuracy. The frequency of AI interaction was a significant factor, with occasional (odds ratio [OR], 8.20; P=.016), fairly frequent (OR, 7.13; P=.033), and very frequent (OR, 8.36; P=.030) use associated with correct identification. Further analysis revealed no significant predictors among the papers' qualities.
Conclusion: Generative AI such as ChatGPT could create medical manuscripts that could not be differentiated from human-authored manuscripts.
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http://dx.doi.org/10.1016/j.mayocp.2024.08.029 | DOI Listing |
Global Spine J
March 2025
Combined Neurosurgical and Orthopaedic Spine Program, University of British Columbia, Vancouver, BC, Canada.
Study DesignNarrative Review.ObjectivesTo summarize the work of the AO Spine Knowledge Forum Tumor, specifically studies from the Epidemiology, Process and Outcomes in Spine Oncology (EPOSO) study.MethodsA narrative review of all published manuscripts from the EPOSO study was undertaken.
View Article and Find Full Text PDFJ Clin Neurosci
March 2025
Department of Obstetrics and Gynecology, Jichi Medical University, 3311-1 Yakushiji, Shimotsuke, Tochigi 329-0498, Japan; Department of Obstetrics and Gynecology, Koga Red Cross Hospital, 1150 Shimoyama, Koga, Ibaraki 306-0014, Japan; Medical Examination Center, Ibaraki Western Medical Center, 555 Otsuka, Chikusei, Ibaraki 308-0813, Japan. Electronic address:
BMJ Evid Based Med
March 2025
Department of Epidemiology, Maastricht University Care and Public Health Research Institute, Maastricht, The Netherlands.
Objective: To evaluate the impact of adding librarians and information specialists (LIS) as methodological peer reviewers to the formal journal peer review process on the quality of search reporting and risk of bias in systematic review searches in the medical literature.
Design: Pragmatic two-group parallel randomised controlled trial.
Setting: Three biomedical journals.
J Thorac Cardiovasc Surg
March 2025
Thoracic Surgery Department, Institute for Clinical & Applied Health Research, University of Hull, Hull, United Kingdom.
Purpose: To compare postoperative activity levels between patients who received an anterior cruciate ligament reconstruction (ACLR) with- and without a lateral extra-articular procedure (LEAP).
Objectives: The primary objective is to examine whether patients treated with an ALCR and LEAP have a greater chance to return to sport (RTS) and return to their pre-injury level of sport (RTPS). The re-rupture rates between the two groups will also be analysed as this is of great influence on the RTS and RTPS.
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