Evidence map›Paper›PMID 39315262›Full record

ArticleResearch square2024

VaxBot-HPV: A GPT-based Chatbot for Answering HPV Vaccine-related Questions.

Cui Tao, Yiming Li, Jianfu Li, Manqi Li, Evan Yu, Muhammad Amith, Lu Tang, Lara Savas, Licong Cui

Abstract readPreprint
In one paragraph

Article in Research square, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

9 authors.

Cui TaoMayo Clinic.
Yiming LiThe University of Texas Health Science Center at Houston.
Jianfu LiMayo Clinic.
Manqi LiThe University of Texas Health Science Center at Houston.
Evan YuThe University of Texas Health Science Center at Houston.
Muhammad AmithThe University of Texas Medical Branch at Galveston.
Lu TangTexas A&M University.
Lara SavasThe University of Texas Health Science Center at Houston.
Licong CuiThe University of Texas Health Science Center at Houston.

Funding

VIOLIN 2.0: Vaccine Information and Ontology LInked kNowledgebaseU24AI171008 · NIAID · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI Yongqun He, Junguk Hur · 2022 to 2026
$4.2M
Dynamic learning for post-vaccine event prediction using temporal information in VAERSR01AI130460 · NIAID · UNIVERSITY OF TEXAS HLTH SCI CTR HOUSTON · PI CHEN, YONG, TAO, CUI · 2017 to 2021
$3.4M
NIAID NIH HHS R01 AI130460NIAID NIH HHS U24 AI171008
6 · The paper itself

Abstract

Background: HPV vaccine is an effective measure to prevent and control the diseases caused by Human Papillomavirus (HPV). This study addresses 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, three 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 (Answer relevancy: 0.85; Faithfulness: 0.97) for the test questions in KB, (Answer relevancy: 0.85; Faithfulness: 0.96) for GPT generated questions. Conclusions: This study underscores the importance of leveraging advanced language models and fine-tuning techniques in the development of chatbots for healthcare applications, with implications for improving medical education and public health communication.

Indexed as

Cervical CancerChatbotGPTHPV vaccineLarge Language modelMedical educationQA systemVaccine

Identifiers

PMID39315262
PMCPMC11419187

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.