ArticleWorld journal of urology2023
ChatGPT and most frequent urological diseases: analysing the quality of information and potential risks for patients.
Article in World journal of urology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers, 2 of them syntheses that pooled it.
What it found
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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.
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
30 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Quality of Cancer-Related Information on New Media (2014-2023): Systematic Review and Meta-Analysis.Journal of medical Internet research · 2025Pooled it
- Large Language Models for Chatbot Health Advice Studies: A Systematic Review.JAMA network open · 2025Pooled it
- Evaluating the quality and readability of AI-generated information on adenomyosis: a comparative analysis of ChatGPT and deepseek regarding query-model consistency.Frontiers in public health · 2026Article
- Evaluation of DeepSeek-R1 and ChatGPT-4o as educational sources for upper tract urothelial carcinoma.Central European journal of urology · 2026Article
- Assessment of patient information quality provided by artificial intelligence-based large language models on cryptorchidism: a comparison of ChatGPT-5, Gemini, and Grok.Revista da Associacao Medica Brasileira (1992) · 2026Article
- Evaluating AI-generated patient education materials for endometrial cancer surgery: a comparative analysis of response quality, reliability, and readability between ChatGPT and DeepSeek models.Frontiers in public health · 2026Article
- Does the Quality and Readability of Information Related to Varicocele Obtained from ChatGPT 4.0 Remain Consistent Across Different Models of Inquiry?The world journal of men's health · 2026Article
- Readability and information quality of LLM-Generated HIV content: a methodological content evaluation.BMC infectious diseases · 2025Article
- Large language model chatbots for patient education in kidney stones: a scoping review.World journal of urology · 2025Article
- Evaluation of prostate cancer pathology reports generated by ChatGPT to enhance patient comprehension.Scientific reports · 2025Article
- Large Language Models in Population Oncology: A Contemporary Review on the Use of Large Language Models to Support Data Collection, Aggregation, and Analysis in Cancer Care and Research.JCO clinical cancer informatics · 2025Review
- The digital dialogue on premature ejaculation: evaluating the efficacy of artificial intelligence-driven responses.International urology and nephrology · 2025Article
- Assessing the Quality and Reliability of ChatGPT's Responses to Radiotherapy-Related Patient Queries: Comparative Study With GPT-3.5 and GPT-4.JMIR cancer · 2025Article
- Medical accuracy of artificial intelligence chatbots in oncology: a scoping review.The oncologist · 2025Article
- AI Chatbots as Sources of STD Information: A Study on Reliability and Readability.Journal of medical systems · 2025Article
- Can ChatGPT provide high-quality patient information on male lower urinary tract symptoms suggestive of benign prostate enlargement?Prostate cancer and prostatic diseases · 2025Article
- Generative AI/LLMs for Plain Language Medical Information for Patients, Caregivers and General Public: Opportunities, Risks and Ethics.Patient preference and adherence · 2025Review
- Capabilities of ChatGPT-3.5 as a Urological Triage System.European urology open science · 2024Article
- Integrating artificial intelligence in renal cell carcinoma: evaluating ChatGPT's performance in educating patients and trainees.Translational cancer research · 2024Article
- A Narrative Review on the Application of Large Language Models to Support Cancer Care and Research.Yearbook of medical informatics · 2024Review
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposeArtificial intelligence (AI) is a set of systems or combinations of algorithms, which mimic human intelligence. ChatGPT is software with artificial intelligence which was recently developed by OpenAI. One of its potential uses could be to consult the information about pathologies and treatments. Our objective was to assess the quality of the information provided by AI like ChatGPT and establish if it is a secure source of information for patients.
methodsQuestions about bladder cancer, prostate cancer, renal cancer, benign prostatic hypertrophy (BPH), and urinary stones were queried through ChatGPT 4.0. Two urologists analysed the responses provided by ChatGPT using DISCERN questionary and a brief instrument for evaluating the quality of informed consent documents.
resultsThe overall information provided in all pathologies was well-balanced. In each pathology was explained its anatomical location, affected population and a description of the symptoms. It concluded with the established risk factors and possible treatment. All treatment answers had a moderate quality score with DISCERN (3 of 5 points). The answers about surgical options contain the recovery time, type of anaesthesia, and potential complications. After analysing all the responses related to each disease, all pathologies except BPH achieved a DISCERN score of 4.
conclusionsChatGPT information should be used with caution since the chatbot does not disclose the sources of information and may contain bias even with simple questions related to the basics of urologic diseases.
Indexed as
Identifiers
37632558What 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.