ArticleJournal of medical systems2024
Responses of Five Different Artificial Intelligence Chatbots to the Top Searched Queries About Erectile Dysfunction: A Comparative Analysis.
Article in Journal of medical systems, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 35 papers.
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.
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Who cites it
35 citing papers in PubMed, 50 citations in OpenAlex.
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- Quality assessment of artificial intelligence responses in erectile dysfunction: a comparative study based on EAU recommendations.International journal of impotence research · 2026Article
- Are AI chatbots ready for chikungunya public education? Evidence on validity, reliability, and readability.BMC public health · 2026Article
- Utilization of artificial intelligence in Men's Health: Opportunities for innovation and quality improvement.International journal of impotence research · 2026Review
- Comment on: Utilization of Artificial Intelligence in Men's Health: Opportunities for Innovation and Quality Improvement.International journal of impotence research · 2026Article
- Evaluation of AI Chatbot Responses to a Standardized Patient Query on Myelin Oligodendrocyte Glycoprotein Antibody-Associated Disease: Cross-Sectional Content Analysis.JMIR medical informatics · 2026Article
- Utilization and prospects of artificial intelligence in the diagnosis, prediction, and treatment of erectile dysfunction.Sexual medicine · 2026Review
- Comparison of online radiologists and large language model chatbots in responding to common radiology-related questions in Chinese: a cross-sectional comparative analysis.Quantitative imaging in medicine and surgery · 2026Article
- From ChatGPT to DeepSeek: assessing the accuracy and readability of AI-generated erectile dysfunction responses.BMC urology · 2026Article
- Comparative evaluation of the quality, reliability, and readability of five large language model responses to frequently asked questions on gestational hypertension.Frontiers in public health · 2026Article
- Artificial Intelligence Chatbots as Sources of Cancer Pain Information: A Comparative Evaluation of Quality, Transparency, and Readability.Journal of pain research · 2026Article
- ZhongdaChat-ED: a medical large language model for personalized erectile dysfunction health consultation and professional clinical decision-making using retrieval-augmented generation.Asian journal of andrology · 2026Article
- Behavior recognition and assessment of spinal dysfunction based on an attention mechanism.Frontiers in medicine · 2026Article
- Evaluation of ChatGPT-5 for Automated ASPECTS Assessment on Non-Contrast CT in Acute Ischemic Stroke.Diagnostics (Basel, Switzerland) · 2025Article
- Readability and information quality of LLM-Generated HIV content: a methodological content evaluation.BMC infectious diseases · 2025Article
- Artificial Intelligence Can Answer Postoperative Questions About Distal Radius Fractures-But Can Patients Understand the Answers?Journal of hand surgery global online · 2025Article
- Observational
- The digital dialogue on premature ejaculation: evaluating the efficacy of artificial intelligence-driven responses.International urology and nephrology · 2025Article
- Evaluating AI chatbots in penis enhancement information: a comparative analysis of readability, reliability and quality.International journal of impotence research · 2025Article
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 at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The aim of the study is to evaluate and compare the quality and readability of responses generated by five different artificial intelligence (AI) chatbots-ChatGPT, Bard, Bing, Ernie, and Copilot-to the top searched queries of erectile dysfunction (ED). Google Trends was used to identify ED-related relevant phrases. Each AI chatbot received a specific sequence of 25 frequently searched terms as input. Responses were evaluated using DISCERN, Ensuring Quality Information for Patients (EQIP), and Flesch-Kincaid Grade Level (FKGL) and Reading Ease (FKRE) metrics. The top three most frequently searched phrases were "erectile dysfunction cause", "how to erectile dysfunction," and "erectile dysfunction treatment." Zimbabwe, Zambia, and Ghana exhibited the highest level of interest in ED. None of the AI chatbots achieved the necessary degree of readability. However, Bard exhibited significantly higher FKRE and FKGL ratings (p = 0.001), and Copilot achieved better EQIP and DISCERN ratings than the other chatbots (p = 0.001). Bard exhibited the simplest linguistic framework and posed the least challenge in terms of readability and comprehension, and Copilot's text quality on ED was superior to the other chatbots. As new chatbots are introduced, their understandability and text quality increase, providing better guidance to patients.
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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.