Will collaborative publishing with ChatGPT drive academic writing in the future?

Ariyaratne, Sisith; Iyengar, Karthikeyan P; Botchu, Rajesh

doi:10.1093/bjs/znad198

Cited by 15 publications

(3 citation statements)

References 4 publications

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“…11 Other shortcomings include the production of texts that have a superficially fluent appearance but contain meaningless collections of medical terms, described as "artificial hallucinations," 17 as well as including faulty and/or fictitious references 18,19 and inaccurate conclusions. 12,13,20,21 Also, because chatbots are in general developed by for-profit companies, there is a lack of transparency in their methodology ("black boxes"), making the assessment of generated data less transparent to the untrained user. 14,21,22 There is currently no clear consensus whether AI-detecting programs commonly used by journal publishers can reliably detect texts prepared by ChatGPT.…”

Section: Manuscript Productionmentioning

confidence: 99%

“…[9][10][11] For example, if prompted with appropriately worded questions and context, ChatGPT is capable of suggesting an appropriate study design or framework. Chatbots are also emerging as helpful tools in developing an appropriate literature search strategy, [12][13][14] in assessing the results of the search 15 or the quality of papers, 14 and in extracting data from papers for further synthesis and analysis. 14,16 A recent concise review and SWOT analysis on the role of ChatGPT in the medical literature during the first 3 months after its release emphasized that it excels in its ability to express ideas and formulate general contexts clearly and comprehensibly, thereby offering an opportunity to assist non-native English speakers in the medical writing process.…”

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confidence: 99%

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Responsible use of chatbots to advance the laboratory hematology scientific literature: Challenges and opportunities

Lucas,

Mackie,

d'Onofrio

et al. 2024

Int J Lab Hematology

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Large language models (LLMs) are artificial neural networks, a particular type of artificial intelligence (AI), trained to recognize complex patterns in natural language or text to generate written content similar to what a human would produce. 1 Chatbots are specific LLM-based applications or interfaces designed to simulate human conversation, generating prompt responses to a variety of inquiries. Chatbots are now offered by several developers, but often differ in data set processing, architecture, training, number of parameters, cost, licensing, and ease of availability, among others. 1 Chat Generative Pre-trained

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Section: Manuscript Productionmentioning

confidence: 99%

mentioning

confidence: 99%

Responsible use of chatbots to advance the laboratory hematology scientific literature: Challenges and opportunities

Lucas,

Mackie,

d'Onofrio

et al. 2024

Int J Lab Hematology

View full text Add to dashboard Cite

show abstract

“…It's crucial to remember that it does acknowledge that AI should play an assistant role [6]. Generally, in a few of minutes or seconds, the AI technology can assist in identifying knowledge gaps, which can make a time significancy [7]. On the other hand, orthopedic evaluation assessments, the residents outperformed ChatGPT-3.5 and GPT-4 in several experimental studies by providing more accurate answers to questions.…”

Section: Introductionmentioning

confidence: 99%

Utility of ChatGPT-4 in Musculoskeletal Imaging: A Narrative Review

Albahkali,

Alawad

2024

Preprint

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Background: With its impressive natural language processing and comprehension skills, ChatGPT-4 (Chat Generative Pre-Trained Transformer) is a technology that shows great promise for use in a number of medical fields. This article provides a thorough description of the possible uses of OpenAI's state-of-the-art language model, ChatGPT-4, in musculoskeletal imaging.Purpose for review: MSK Radiologists need to evolve about their knowledge and understanding of the roles of ChatGPT and its implications in daily practice. We aim to emphasize the advantages of ChatGPT-4 on the musculoskeletal imaging field and its potential to enhance radiologist working checklist review items, and the overall productivity of radiology reports. Recent findings:The fact of that specialists in radiology, rheumatology, orthopedic surgery, and other fields are conversant with ChatGPT. Furthermore, opinions are generally well, despite the fact that many people have reservations about the new technology, which is still developing [1].

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Generative AI and simulation modeling: how should you (not) use large language models like ChatGPT

Akhavan,

Jalali

2024

System Dynamics Review

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Generative Artificial Intelligence (AI) tools, such as Large Language Models (LLMs) and chatbots like ChatGPT, hold promise for advancing simulation modeling. Despite their growing prominence and associated debates, there remains a gap in comprehending the potential of generative AI in this field and a lack of guidelines for its effective deployment. This article endeavors to bridge these gaps. We discuss the applications of ChatGPT through an example of modeling COVID‐19's impact on economic growth in the United States. However, our guidelines are generic and can be applied to a broader range of generative AI tools. Our work presents a systematic approach for integrating generative AI across the simulation research continuum, from problem articulation to insight derivation and documentation, independent of the specific simulation modeling method. We emphasize while these tools offer enhancements in refining ideas and expediting processes, they should complement rather than replace critical thinking inherent to research. © 2024 The Authors. System Dynamics Review published by John Wiley & Sons Ltd on behalf of System Dynamics Society.

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Will collaborative publishing with ChatGPT drive academic writing in the future?

Cited by 15 publications

References 4 publications

Responsible use of chatbots to advance the laboratory hematology scientific literature: Challenges and opportunities

Responsible use of chatbots to advance the laboratory hematology scientific literature: Challenges and opportunities

Utility of ChatGPT-4 in Musculoskeletal Imaging: A Narrative Review

Generative AI and simulation modeling: how should you (not) use large language models like ChatGPT

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