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With breakthroughs in Natural Language Processing and Artificial Intelligence (AI), the usage of Large Language Models (LLMs) in academic research has increased tremendously. Models such as Generative Pre-trained Transformer (GPT) are used by researchers in literature review, abstract screening, and manuscript drafting. However, these models also present the attendant challenge of providing ethically questionable scientific information. Our study provides a snapshot of global researchers' perception of current trends and future impacts of LLMs in research. Using a cross-sectional design, we surveyed 226 medical and paramedical researchers from 59 countries across 65 specialties, trained in the Global Clinical Scholars' Research Training certificate program of Harvard Medical School between 2020 and 2024. Majority (57.5%) of these participants practiced in an academic setting with a median of 7 (2,18) PubMed Indexed published articles. 198 respondents (87.6%) were aware of LLMs and those who were aware had higher number of publications (p 

Original publication

DOI

10.1038/s41598-024-81370-6

Type

Journal article

Journal

Sci Rep

Publication Date

30/12/2024

Volume

14

Keywords

Academic writing, Artificial intelligence, Biomedical research, Large language models, Humans, Artificial Intelligence, Cross-Sectional Studies, Research Personnel, Male, Biomedical Research, Female, Natural Language Processing, Publishing, Adult, Language, Surveys and Questionnaires