In one paragraphArticle in BMC oral health, 2025. 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 itWhat 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 registryThe 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 literatureWho cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
4 · The recordCorrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
5 · Who and what moneyAuthors and funding
8 authors.
Yu-Tao XiongState Key Laboratory of Oral Diseases & National Center for Stomatology & National Clinical Research Center for Oral Diseases & Sichuan Provincial Engineering Research Center of Smart Diagnosis and Treatment for Oral Diseases & Department of Oral and Maxillofacial Surgery, West China Hospital of Stomatology, Sichuan University, Chengdu, 610041, China.ORCID http://orcid.org/0000-0003-1257-4055 Hao-Nan LiuState Key Laboratory of Oral Diseases & National Center for Stomatology & National Clinical Research Center for Oral Diseases & Sichuan Provincial Engineering Research Center of Smart Diagnosis and Treatment for Oral Diseases & Department of Oral and Maxillofacial Surgery, West China Hospital of Stomatology, Sichuan University, Chengdu, 610041, China.ORCID http://orcid.org/0009-0007-5175-0724 Yu-Min ZengState Key Laboratory of Oral Diseases & National Center for Stomatology & National Clinical Research Center for Oral Diseases & Sichuan Provincial Engineering Research Center of Smart Diagnosis and Treatment for Oral Diseases & Department of Oral and Maxillofacial Surgery, West China Hospital of Stomatology, Sichuan University, Chengdu, 610041, China.ORCID http://orcid.org/0009-0004-1257-6135 Zheng-Zhe ZhanState Key Laboratory of Oral Diseases & National Center for Stomatology & National Clinical Research Center for Oral Diseases & Sichuan Provincial Engineering Research Center of Smart Diagnosis and Treatment for Oral Diseases & Department of Oral and Maxillofacial Surgery, West China Hospital of Stomatology, Sichuan University, Chengdu, 610041, China.ORCID http://orcid.org/0009-0008-2659-9943 Wei LiuState Key Laboratory of Oral Diseases & National Center for Stomatology & National Clinical Research Center for Oral Diseases & Sichuan Provincial Engineering Research Center of Smart Diagnosis and Treatment for Oral Diseases & Department of Oral and Maxillofacial Surgery, West China Hospital of Stomatology, Sichuan University, Chengdu, 610041, China.ORCID http://orcid.org/0000-0002-1470-3538 Yuan-Chen WangState Key Laboratory of Oral Diseases & National Center for Stomatology & National Clinical Research Center for Oral Diseases & Sichuan Provincial Engineering Research Center of Smart Diagnosis and Treatment for Oral Diseases & Department of Oral and Maxillofacial Surgery, West China Hospital of Stomatology, Sichuan University, Chengdu, 610041, China.ORCID http://orcid.org/0009-0007-2813-4034 Wei TangState Key Laboratory of Oral Diseases & National Center for Stomatology & National Clinical Research Center for Oral Diseases & Sichuan Provincial Engineering Research Center of Smart Diagnosis and Treatment for Oral Diseases & Department of Oral and Maxillofacial Surgery, West China Hospital of Stomatology, Sichuan University, Chengdu, 610041, China. mydrtw@vip.sina.com.ORCID http://orcid.org/0000-0001-7568-2884 Chang LiuState Key Laboratory of Oral Diseases & National Center for Stomatology & National Clinical Research Center for Oral Diseases & Sichuan Provincial Engineering Research Center of Smart Diagnosis and Treatment for Oral Diseases & Department of Oral and Maxillofacial Surgery, West China Hospital of Stomatology, Sichuan University, Chengdu, 610041, China. liu_chang_92@sina.com.ORCID http://orcid.org/0000-0002-1232-8308 Funding
National Health Commission Hospital Management Institute "Clinical Application Research Project on Medical Artificial Intelligence" YLXX24AIA009Research and Develop Program, West China Hospital of Stomatology Sichuan University RD-03-202303Sichuan Science and Technology Program 2024NSFSC0659
6 · The paper itselfAbstract
backgroundGenerative artificial intelligence (GenAI) has demonstrated potential in remote consultations, yet its capacity to comprehend oral cancer has not yet been fully evaluated. The objective of this study was to evaluate the accuracy, reliability and validity of GenAI in addressing questions related to remote consultations for oral cancer.
methodsA search was conducted on telemedicine platforms in China, summarizing patients' inquiries regarding oral cancer. A panel of board-certified oral surgeons compiled the reference answers for addressing these questions. GPT-3.5-turbo and GPT-4o were tasked to answer specific questions related to oral cancer, with their responses recorded. The responses were assessed using qualitative and quantitative measures, including the accuracy, the number of key points, text length, lexical density, and a Likert scale. The chi-square test was utilized to detect differences in qualitative data, while Kruskal-Wallis test, Mann-Whitney U test and t-test for quantitative data.
resultsA total of 34 oral cancer questions were included, covering basic, etiology, diagnosis, intervention, and prognosis. GPT-3.5-Turbo demonstrated an overall accuracy rate of 77.50% in qualitative analysis, and GPT-4o was 88.20%. The average scores of GPT-3.5Turbo and GPT-4o were 3.96 and 4.35, respectively, with statistically significant differences. GPT-3.5-Turbo and GPT-4o were close to the reference answers in terms of the number of key points, but significantly lower in terms of text length and lexical density.
conclusionGPT-4o demonstrated a marginal advantage, although no statistically significant differences in response accuracy were observed between GPT-3.5-Turbo and GPT-4o. Moreover, GPT-4o outperformed in terms of reliability and validity, making it more appropriate for remote consultation scenarios.
Indexed as
Artificial IntelligenceMouth NeoplasmsRemote ConsultationChinaHumansReproducibility of ResultsChatGPTGenerative artificial intelligenceGPT-4Natural language processingOral CancerTelemedicine
Identifiers
PMID39979918
PMCPMC11844040
What Socratic holds
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LicenceCC BY-NC-ND
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