ArticleJAMIA open2025
VaxBot-HPV: a GPT-based chatbot for answering HPV vaccine-related questions.
Article in JAMIA open, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
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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
19 citing papers in PubMed.
- Age- and sex-related variation in ChatGPT-4o HPV vaccine recommendation style: A fixed-prompt audit.Human vaccines & immunotherapeutics · 2026Article
- Generative large language models in medicine: a scoping review of recent methodological advances.npj health systems · 2026Review
- Precision pharmacology: deep learning infused ontological framework with E-GRU enhancement for tailored medicine prescriptions.Scientific reports · 2026Article
- Vaccine communication: a critical review of foundations, challenges, and future directions.NPJ vaccines · 2026Review
- Structured taxonomy and framework for developing medical benchmark in large language models derived from scoping review.NPJ digital medicine · 2026Article
- Examining Artificial Intelligence Chatbots' Responses in Providing Human Papillomavirus Vaccine Information for Young Adults: Qualitative Content Analysis.JMIR public health and surveillance · 2026Article
- Training the public health workforce for generative AI: validation of the Italian Chatbot Usability Questionnaire.Frontiers in public health · 2026Article
- Optimizing HIV Care Engagement: Usability of a mHealth App for Identifying and Retaining Individuals with Nonviral Suppression in Digital Cohort.Applied clinical informatics · 2026Article
- Exploring multimodal large language models on transthoracic Echocardiogram (TTE) tasks for cardiovascular decision support.Journal of biomedical informatics · 2025Article
- Comparing artificial intelligence- vs clinician-authored summaries of simulated primary care electronic health records.JAMIA open · 2025Article
- Design and Validation of a Chatbot-Based Cervical Cancer Screening Decision Aid for Women Experiencing Socioeconomic Disadvantage: User-Centered Approach Study.JMIR cancer · 2025Article
- Reproducible generative artificial intelligence evaluation for health care: a clinician-in-the-loop approach.JAMIA open · 2025Article
- A Culturally Tailored Artificial Intelligence Chatbot (K-Bot) to Promote Human Papillomavirus Vaccination Among Korean Americans: Development and Usability Study.Asian/Pacific Island nursing journal · 2025Article
- Enhancing Relation Extraction for COVID-19 Vaccine Shot-Adverse Event Associations with Large Language Models.Research square · 2025Article
- Exploring Associations Between COVID-19 Bivalent Vaccines and Their Related Adverse Events: A Correlational Study.Research square · 2025Article
- Exploring Temporal and Spatial Characteristics of Serious Adverse Event Reports Following COVID-19 Bivalent Vaccines.Research square · 2025Article
- Improving entity recognition using ensembles of deep learning and fine-tuned large language models: A case study on adverse event extraction from VAERS and social media.Journal of biomedical informatics · 2025Article
- Real-world pharmacovigilance reports of hepatitis A inactivated and hepatitis B (recombinant) vaccine: insights from disproportionality analysis of the vaccine adverse event reporting system.Frontiers in cellular and infection microbiology · 2025Article
- Risk signal assessment of Tdap vaccine use alone by pregnant women: An updated pharmacoepidemiological study.Frontiers in cellular and infection microbiology · 2025Article
Corrections and comments
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Authors and funding
10 authors.
Funding
Abstract
Objective: Human Papillomavirus (HPV) vaccine is an effective measure to prevent and control the diseases caused by HPV. However, widespread misinformation and vaccine hesitancy remain significant barriers to its uptake. This study focuses on the development of VaxBot-HPV, a chatbot aimed at improving health literacy and promoting vaccination uptake by providing information and answering questions about the HPV vaccine. Methods: We constructed the knowledge base (KB) for VaxBot-HPV, which consists of 451 documents from biomedical literature and web sources on the HPV vaccine. We extracted 202 question-answer pairs from the KB and 39 questions generated by GPT-4 for training and testing purposes. To comprehensively understand the capabilities and potential of GPT-based chatbots, 3 models were involved in this study: GPT-3.5, VaxBot-HPV, and GPT-4. The evaluation criteria included answer relevancy and faithfulness. Results: VaxBot-HPV demonstrated superior performance in answer relevancy and faithfulness compared to baselines. For test questions in KB, it achieved an answer relevancy score of 0.85 and a faithfulness score of 0.97. Similarly, it attained scores of 0.85 for answer relevancy and 0.96 for faithfulness on GPT-generated questions. Discussion: VaxBot-HPV demonstrates the effectiveness of fine-tuned large language models in healthcare, outperforming generic GPT models in accuracy and relevance. Fine-tuning mitigates hallucinations and misinformation, ensuring reliable information on HPV vaccination while allowing dynamic and tailored responses. The specific fine-tuning, which includes context in addition to question-answer pairs, enables VaxBot-HPV to provide explanations and reasoning behind its answers, enhancing transparency and user trust. Conclusions: This study underscores the importance of leveraging large language models and fine-tuning techniques in the development of chatbots for healthcare applications, with implications for improving medical education and public health communication.
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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.