ArticleOman medical journal2026
Assessing the Accuracy of ChatGPT's Answers to Basic Questions on Uterine and Cervical Cancers.
Article in Oman medical journal, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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.
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
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Objectives: Artificial intelligence (AI) platforms based on large language models such as ChatGPT, are increasingly being used by both the public and medical professionals to obtain medical information. This rapid growth in reliance makes it essential to systematically evaluate the accuracy and clinical reliability of AI-generated medical content. The objective of this study was to evaluate the accuracy of responses provided by ChatGPT regarding prevention, screening, treatment, and risk factors of common gynecological cancers. The assessment focused primarily on the use of ChatGPT by primary care providers and the public with limited subject-specific knowledge. Methods: We evaluated the reliability of ChatGPT (version 3.5) in answering questions about two of the most common gynecological cancers. ChatGPT was posed a total of 40 questions on the prevention, screening, and treatment of endometrial cancer (20 questions) and cervical cancer (20 questions). Responses were independently reviewed and categorized as accurate, inadequate, or inaccurate by five physicians with a mean of 18 ± 3 years of experience in gynecological oncology. Reviewers provided reasons for deeming some responses as inadequate or inaccurate. Results: Overall, 20 out of 40 (50%) responses by ChatGPT 3.5 were regarded as either inaccurate or inadequate. Most of the deficient responses were related to questions on the treatment of the two cancers, while responses to questions about prevention were mostly accurate. Conclusions Ch: atGPT may provide accurate information about prevention of gynecological cancers, but the public and health professionals should not rely on its responses to make medical decisions, as many responses in this domain were inadequate or inaccurate. Consultation with qualified physicians or specialists is essential for individualized decision-making. Medical information sourced from AI tools such as ChatGPT should be integrated with clinician oversight to improve reliability.
Indexed as
Identifiers
What OpenQuestion holds
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.