ArticleCureus2023
The Readiness of ChatGPT to Write Scientific Case Reports Independently: A Comparative Evaluation Between Human and Artificial Intelligence.
Article in Cureus, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
14 citing papers in PubMed.
- Trial
- The Ethics of Authorship.The Ulster medical journal · 2026Article
- Assessing Large Language Models for Early Article Identification in Otolaryngology-Head and Neck Surgery Systematic Reviews.Health care science · 2026Article
- Survey of Guidance for Authors on the Use of Generative Artificial Intelligence in Pharmaceutical Journals.The Canadian journal of hospital pharmacy · 2026Article
- Will ChatGPT-4 improve the quality of medical abstracts?Paediatrics & child health · 2025Article
- Article
- Artificial intelligence-assisted academic writing: recommendations for ethical use.Advances in simulation (London, England) · 2025Article
- Is your curriculum GenAI-proof? A method for GenAI impact assessment and a case study.MedEdPublish (2016) · 2025Article
- The transformative impact of large language models on medical writing and publishing: current applications, challenges and future directions.The Korean journal of physiology & pharmacology : official journal of the Korean Physiological Society and the Korean Society of Pharmacology · 2024Review
- Reference Hallucination Score for Medical Artificial Intelligence Chatbots: Development and Usability Study.JMIR medical informatics · 2024Article
- Readability analysis of ChatGPT's responses on lung cancer.Scientific reports · 2024Article
- Article
- Clinical Research With Large Language Models Generated Writing-Clinical Research with AI-assisted Writing (CRAW) Study.Critical care explorations · 2023Article
- Medical Students' Perceptions of Large Language Models in Healthcare: A Multinational Cross-Sectional Study.Journal of medical education and curricular developmentArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The use of artificial intelligence (AI) in scientific publishing has gained increased attention, and one AI tool that has been the subject of much discussion is ChatGPT. It is a large language model (LLM) built on the OpenAI platform that aims to emulate human-like writing and continually improves through user interactions. In this paper, ChatGPT's performance was assessed in medical publishing by comparing it to a case report written by oral and maxillofacial radiologists. ChatGPT was tasked with writing a case report based on a drafted report written by the authors in five different prompts. The findings of this study highlight issues related to the accuracy, completeness, and readability of the generated text. These results have significant implications for the future use of AI in scientific publishing and suggest that in the current iteration of ChatGPT, scientific information must be revised by an expert.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.