ArticleJournal of medical Internet research2023
Potential and Limitations of ChatGPT 3.5 and 4.0 as a Source of COVID-19 Information: Comprehensive Comparative Analysis of Generative and Authoritative Information.
Article in Journal of medical Internet research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed.
- Assessment of ChatGPT-4.0 versus ChatGPT-Mini in Generating Guideline-Based Hypertension Content.Arquivos brasileiros de cardiologia · 2026Article
- Article
- Human evaluation of large language models in healthcare: gaps, challenges, and the need for standardization.npj health systems · 2025Article
- Evaluating chat generative pretrained transformer in answering questions on endoscopic mucosal resection and endoscopic submucosal dissection.World journal of gastrointestinal oncology · 2025Article
- Evaluating evidence-based health information from generative AI using a cross-sectional study with laypeople seeking screening information.NPJ digital medicine · 2025Article
- Identification of Online Health Information Using Large Pretrained Language Models: Mixed Methods Study.Journal of medical Internet research · 2025Article
- Using Large Language Models to Retrieve Critical Data from Clinical Processes and Business Rules.Bioengineering (Basel, Switzerland) · 2024Article
- AI in Dental Radiology-Improving the Efficiency of Reporting With ChatGPT: Comparative Study.Journal of medical Internet research · 2024Article
- eHealth Assistant AI Chatbot Using a Large Language Model to Provide Personalized Answers through Secure Decentralized Communication.Sensors (Basel, Switzerland) · 2024Article
- Comparative performance analysis of large language models: ChatGPT-3.5, ChatGPT-4 and Google Gemini in glucocorticoid-induced osteoporosis.Journal of orthopaedic surgery and research · 2024Article
- Comparing GPT-4 and Human Researchers in Health Care Data Analysis: Qualitative Description Study.Journal of medical Internet research · 2024Article
- Comparison of Medical Research Abstracts Written by Surgical Trainees and Senior Surgeons or Generated by Large Language Models.JAMA network open · 2024Article
- Medical knowledge of ChatGPT in public health, infectious diseases, COVID-19 pandemic, and vaccines: multiple choice questions examination based performance.Frontiers in public health · 2024Article
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Authors and funding
7 authors.
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Abstract
backgroundThe COVID-19 pandemic, caused by the SARS-CoV-2 virus, has necessitated reliable and authoritative information for public guidance. The World Health Organization (WHO) has been a primary source of such information, disseminating it through a question and answer format on its official website. Concurrently, ChatGPT 3.5 and 4.0, a deep learning-based natural language generation system, has shown potential in generating diverse text types based on user input.
objectiveThis study evaluates the accuracy of COVID-19 information generated by ChatGPT 3.5 and 4.0, assessing its potential as a supplementary public information source during the pandemic.
methodsWe extracted 487 COVID-19-related questions from the WHO's official website and used ChatGPT 3.5 and 4.0 to generate corresponding answers. These generated answers were then compared against the official WHO responses for evaluation. Two clinical experts scored the generated answers on a scale of 0-5 across 4 dimensions-accuracy, comprehensiveness, relevance, and clarity-with higher scores indicating better performance in each dimension. The WHO responses served as the reference for this assessment. Additionally, we used the BERT (Bidirectional Encoder Representations from Transformers) model to generate similarity scores (0-1) between the generated and official answers, providing a dual validation mechanism.
resultsThe mean (SD) scores for ChatGPT 3.5-generated answers were 3.47 (0.725) for accuracy, 3.89 (0.719) for comprehensiveness, 4.09 (0.787) for relevance, and 3.49 (0.809) for clarity. For ChatGPT 4.0, the mean (SD) scores were 4.15 (0.780), 4.47 (0.641), 4.56 (0.600), and 4.09 (0.698), respectively. All differences were statistically significant (P<.001), with ChatGPT 4.0 outperforming ChatGPT 3.5. The BERT model verification showed mean (SD) similarity scores of 0.83 (0.07) for ChatGPT 3.5 and 0.85 (0.07) for ChatGPT 4.0 compared with the official WHO answers.
conclusionsChatGPT 3.5 and 4.0 can generate accurate and relevant COVID-19 information to a certain extent. However, compared with official WHO responses, gaps and deficiencies exist. Thus, users of ChatGPT 3.5 and 4.0 should also reference other reliable information sources to mitigate potential misinformation risks. Notably, ChatGPT 4.0 outperformed ChatGPT 3.5 across all evaluated dimensions, a finding corroborated by BERT model validation.
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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.