Evidence map›Paper›PMID 40396096›Full record

ArticleJournal of family medicine and primary care2025

Discussion of the ability to use chatGPT to answer questions related to esophageal cancer of patient concern.

Fengxia Yu, Mingyu Lei, Shiyu Wang, Miao Liu, Xiao Fu, Yuan Yu

Abstract read
In one paragraph

Article in Journal of family medicine and primary care, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

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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.

2 · The registry

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3 · Its place in the literature

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4 · The record

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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

6 authors.

Fengxia YuDepartment of Thoracic Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Mingyu LeiDepartment of Thoracic Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Shiyu WangDepartment of Thoracic Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Miao LiuDepartment of Thoracic Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Xiao FuDepartment of Thoracic Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Yuan YuDepartment of Thoracic Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Chat Generation Pre-Trained Converter (ChatGPT) is a language processing model based on artificial intelligence (AI). It covers a wide range of topics, including medicine, and can provide patients with knowledge about esophageal cancer. Objective: Based on its risk, this study aimed to assess ChatGPT's accuracy in answering patients' questions about esophageal cancer. Methods: By referring to professional association websites, social software and the author's clinical experience, 55 questions concerned by Chinese patients and their families were generated and scored by two deputy chief physicians of esophageal cancer. The answers were: (1) comprehensive/correct, (2) incomplete/partially correct, (3) partially accurate, partially inaccurate, and (4) completely inaccurate/irrelevant. Score differences are resolved by a third reviewer. Results: Out of 55 questions, 24 (43.6%) of the answers provided by ChatGPT were complete and correct, 13 (23.6%) were correct but incomplete, 18 (32.7%) were partially wrong, and no answers were completely wrong. Comprehensive and correct answers were highest in the field of prevention (50 percent), while partially incorrect answers were highest in the field of treatment (77.8 percent). Conclusion: ChatGPT can accurately answer the questions about the prevention and diagnosis of esophageal cancer, but it cannot accurately answer the questions about the treatment and prognosis of esophageal cancer. Further investigation and refinement of this widely used large-scale language model are needed before it can be recommended to patients with esophageal cancer, and ongoing research is still needed to verify the safety and accuracy of these tools and their medical applications.

Indexed as

ChatGPTdiscussiondisease managementesophageal cancerpatient concerntelemedicine

Identifiers

PMID40396096
PMCPMC12088566

What OpenQuestion holds

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Registered trials

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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.