Evidence map›Paper›PMID 37933835›Full record

ArticleUrology research & practice2023

Assessing the Performance of Chat Generative Pretrained Transformer (ChatGPT) in Answering Andrology-Related Questions.

Ufuk Caglar, Oguzhan Yildiz, M Fırat Ozervarli, Resat Aydin, Omer Sarilar, Faruk Ozgor, Mazhar Ortac

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Article in Urology research & practice, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
16citing 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

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

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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

7 authors.

Ufuk CaglarDepartment of Urology, Haseki Training and Research Hospital, Istanbul, Turkey.
Oguzhan YildizDepartment of Urology, Haseki Training and Research Hospital, Istanbul, Turkey.
M Fırat OzervarliDepartment of Urology, Istanbul University, Istanbul School of Medicine, Istanbul, Turkey.
Resat AydinDepartment of Urology, Istanbul University, Istanbul School of Medicine, Istanbul, Turkey.
Omer SarilarDepartment of Urology, Haseki Training and Research Hospital, Istanbul, Turkey.
Faruk OzgorDepartment of Urology, Haseki Training and Research Hospital, Istanbul, Turkey.
Mazhar OrtacDepartment of Urology, Istanbul University, Istanbul School of Medicine, Istanbul, Turkey.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveThe internet and social media have become primary sources of health information, with men frequently turning to these platforms before seeking professional help. Chat generative pretrained transformer (ChatGPT), an artificial intelligence model developed by OpenAI, has gained popularity as a natural language processing program. The present study evaluated the accuracy and reproducibility of ChatGPT's responses to andrology-related questions.

methodsThe study analyzed frequently asked andrology questions from health forums, hospital websites, and social media platforms like YouTube and Instagram. Questions were categorized into topics like male hypogonadism, erectile dysfunction, etc. The European Association of Urology (EAU) guideline recommendations were also included. These questions were input into ChatGPT, and responses were evaluated by 3 experienced urologists who scored them on a scale of 1 to 4.

resultsOut of 136 evaluated questions, 108 met the criteria. Of these, 87.9% received correct and adequate answers, 9.3% were correct but insufficient, and 3 responses contained both correct and incorrect information. No question was answered completely wrong. The highest correct answer rates were for disorders of ejaculation, penile curvature, and male hypogonadism. The EAU guideline-based questions achieved a correctness rate of 86.3%. The reproducibility of the answers was over 90%.

conclusionThe study found that ChatGPT provided accurate and reliable answers to over 80% of andrology-related questions. While limitations exist, such as potential outdated data and inability to understand emotional aspects, ChatGPT's potential in the health-care sector is promising. Collaborating with health-care professionals during artificial intelligence model development could enhance its reliability.

Identifiers

PMID37933835
PMCPMC10765186

What OpenQuestion holds

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LicenceCC BY
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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.