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Can ChatGPT draft a research article? An example of population-level vaccine effectiveness analysis
Open accessAbstract
We reflect on our experiences of using Generative Pre-trained Transformer ChatGPT, a chatbot launched by OpenAI in November 2022, to draft a research article. We aim to demonstrate how ChatGPT could help researchers to accelerate drafting their papers. We created a simulated data set of 100 000 health care workers with varying ages, Body Mass Index (BMI), and risk profiles. Simulation data allow analysts to test statistical analysis techniques, such as machine-learning based approaches, without compromising patient privacy. Infections were simulated with a randomized probability of hospitalisation. A subset of these fictitious people was vaccinated with a fictional vaccine that reduced this probability of hospitalisation after infection. We then used ChatGPT to help us decide how to handle the simulated data in order to determine vaccine effectiveness and draft a related research paper. AI-based language models in data analysis and scientific writing are an area of growing interest, and this exemplar analysis aims to contribute to the understanding of how ChatGPT can be used to facilitate these tasks.
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“Additionally, utilizing GAI tools introduces the risk of plagiarism, when text is duplicated from data sources.12 33”
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“ChatGPT’s GPT-3.5 iteration has already shown promise in several routine medical tasks and medical research [4-7], even raising ethical concerns in the literature [2,3,8].”
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Metadata
- Authors
- Macdonald, C., Adeloye, D., Sheikh, A., & Rudan, I.
- Affiliations
- University of Edinburgh (GB)
- Corresponding author
- Rudan, Igor
- Venue
- Journal of Global Health
- Published
- 2023-02-17
- Volume
- 13
- Pages
- 01003-01003
- ISSN
- 2047-2978 (ISSN-L)
- 2047-2986
- PMC
- PMC9936200
- OpenAlex
- W4321167341
- Cited by
- 243
- References
- 10
- Citations by year
- 2026: 18 · 2025: 44 · 2024: 87 · 2023: 93
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- cc-by
- Locations
- Journal of Global Health (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Edinburgh Research Explorer (University of Edinburgh) (submittedVersion, cc-by)
- Topics
- Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
- Social Sciences › Library and Information Sciences › Academic Writing and Publishing
- Physical Sciences › Computer Science › Artificial Intelligence › Artificial Intelligence Applications
- Keywords
- ChatGPT, generative AI, scientific writing, vaccine effectiveness, population-level analysis, simulated data, healthcare workers, hospitalization
- MeSH terms
- Vaccine Efficacy, Computer Simulation, Confidentiality, Health Personnel, Humans, Software
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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