Evidence map›Paper›PMID 39098480›Full record

ArticleInternational dental journal2025

Assessing the Capabilities of Generative Pretrained Transformer-4 in Addressing Open-Ended Inquiries of Oral Cancer.

Kaiyuan Ji, Jing Han, Guangtao Zhai, Jiannan Liu

Abstract read
In one paragraph

Article in International dental journal, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed, 1 pooled it
–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

3 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Transformer-based models in dentistry: a systematic review.BMC medical informatics and decision making · 2026
    Pooled it
  2. Article
  3. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Kaiyuan JiCollege of Information Science and Technology, Beijing University of Chemical Technology, Beijing, China.
Jing HanDepartment of Oral and Maxillofacial Head and Neck Oncology, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Guangtao ZhaiSchool of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University, Shanghai, China. Electronic address: zhaiguangtao@sjtu.edu.cn.
Jiannan LiuDepartment of Oral and Maxillofacial Head and Neck Oncology, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China. Electronic address: laurence_ljn@163.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

INTRODUCTION AND

aimsIn the face of escalating oral cancer rates, the application of large language models like Generative Pretrained Transformer (GPT)-4 presents a novel pathway for enhancing public awareness about prevention and early detection. This research aims to explore the capabilities and possibilities of GPT-4 in addressing open-ended inquiries in the field of oral cancer.

methodsUsing 60 questions accompanied by reference answers, covering concepts, causes, treatments, nutrition, and other aspects of oral cancer, evaluators from diverse backgrounds were selected to evaluate the capabilities of GPT-4 and a customized version. A P value under .05 was considered significant.

resultsAnalysis revealed that GPT-4 and its adaptations notably excelled in answering open-ended questions, with the majority of responses receiving high scores. Although the median score for standard GPT-4 was marginally better, statistical tests showed no significant difference in capabilities between the two models (P > .05). Despite statistical significance indicated diverse backgrounds of evaluators have statistically difference (P < .05), a post hoc test and comprehensive analysis demonstrated that both editions of GPT-4 demonstrated equivalent capabilities in answering questions concerning oral cancer.

conclusionsGPT-4 has demonstrated its capability to furnish responses to open-ended inquiries concerning oral cancer. Utilizing this advanced technology to boost public awareness about oral cancer is viable and has much potential. When it's unable to locate pertinent information, it will resort to their inherent knowledge base or recommend consulting professionals after offering some basic information. Therefore, it cannot supplant the expertise and clinical judgment of surgical oncologists and could be used as an adjunctive evaluation tool.

Indexed as

Mouth NeoplasmsEarly Detection of CancerHumansSurveys and QuestionnairesArtificial intelligenceEducation toolGPT-4Oral cancerOral health

Identifiers

PMID39098480
PMCPMC11806334

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.