Skeletal infections: microbial pathogenesis, immunity and clinical management.

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Abstract

[Indexed for MEDLINE] Conflict of interest statement: The authors declare no competing interests. 2. Curr Osteoporos Rep. 2024 Feb;22(1):115-121. doi: 10.1007/s11914-023-00852-0. Epub 2024 Jan 16. The Use of Artificial Intelligence in Writing Scientific Review Articles. Kacena MA(1)(2)(3)(4), Plotkin LI(5)(6)(7), Fehrenbacher JC(8)(9)(10). Author information: (1)Department of Orthopaedic Surgery, Indiana University School of Medicine, Indianapolis, IN, 46202, USA. mkacena@iupui.edu. (2)Department of Anatomy, Cell Biology & Physiology, Indiana University School of Medicine, Indianapolis, IN, 46202, USA. mkacena@iupui.edu. (3)Indiana Center for Musculoskeletal Health, Indiana University School of Medicine, Indianapolis, IN, 46202, USA. mkacena@iupui.edu. (4)Richard L. Roudebush VA Medical Center, Indianapolis, IN, 46202, USA. mkacena@iupui.edu. (5)Department of Anatomy, Cell Biology & Physiology, Indiana University School of Medicine, Indianapolis, IN, 46202, USA. (6)Indiana Center for Musculoskeletal Health, Indiana University School of Medicine, Indianapolis, IN, 46202, USA. (7)Richard L. Roudebush VA Medical Center, Indianapolis, IN, 46202, USA. (8)Indiana Center for Musculoskeletal Health, Indiana University School of Medicine, Indianapolis, IN, 46202, USA. jfehrenb@iu.edu. (9)Department of Pharmacology and Toxicology, Indiana University School of Medicine, Indianapolis, IN, 46202, USA. jfehrenb@iu.edu. (10)Stark Neuroscience Research Institute, Indiana University School of Medicine, Indianapolis, IN, 46202, USA. jfehrenb@iu.edu. PURPOSE OF REVIEW: With the recent explosion in the use of artificial intelligence (AI) and specifically ChatGPT, we sought to determine whether ChatGPT could be used to assist in writing credible, peer-reviewed, scientific review articles. We also sought to assess, in a scientific study, the advantages and limitations of using ChatGPT for this purpose. To accomplish this, 3 topics of importance in musculoskeletal research were selected: (1) the intersection of Alzheimer's disease and bone; (2) the neural regulation of fracture healing; and (3) COVID-19 and musculoskeletal health. For each of these topics, 3 approaches to write manuscript drafts were undertaken: (1) human only; (2) ChatGPT only (AI-only); and (3) combination approach of #1 and #2 (AI-assisted). Articles were extensively fact checked and edited to ensure scientific quality, resulting in final manuscripts that were significantly different from the original drafts. Numerous parameters were measured throughout the process to quantitate advantages and disadvantages of approaches. RECENT FINDINGS: Overall, use of AI decreased the time spent to write the review article, but required more extensive fact checking. With the AI-only approach, up to 70% of the references cited were found to be inaccurate. Interestingly, the AI-assisted approach resulted in the highest similarity indices suggesting a higher likelihood of plagiarism. Finally, although the technology is rapidly changing, at the time of study, ChatGPT 4.0 had a cutoff date of September 2021 rendering identification of recent articles impossible. Therefore, all literature published past the cutoff date was manually provided to ChatGPT, rendering approaches #2 and #3 identical for contemporary citations. As a result, for the COVID-19 and musculoskeletal health topic, approach #2 was abandoned midstream due to the extensive overlap with approach #3. The main objective of this scientific study was to see whether AI could be used in a scientifically appropriate manner to improve the scientific writing process. Indeed, AI reduced the time for writing but had significant inaccuracies. The latter necessitates that AI cannot currently be used alone but could be used with careful oversight by humans to assist in writing scientific review articles. © 2024. This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply. DOI: 10.1007/s11914-023-00852-0 PMCID: PMC10912250