ArticleBMC urology2026
From ChatGPT to DeepSeek: assessing the accuracy and readability of AI-generated erectile dysfunction responses.
Article in BMC urology, 2026. 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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5 authors.
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Abstract
backgroundThis study aims to compare responses generated by DeepSeek, a new large language model, and ChatGPT to erectile dysfunction (ED)–related questions.
methodsThe study was conducted by posing online queries to both ChatGPT-4o (OpenAI, United States) and DeepSeek V3 (Hangzhou DeepSeek Artificial Intelligence, China). The most frequently asked questions about ED were identified using Google Trends. The responses from both artificial intelligence (AI) were evaluated by three board-certified urologists, who rated their accuracy on a scale of 1 to 4. Readability was assessed using the Flesch Reading Ease Score (FRES), Flesch-Kincaid Grade Level (FKGL), and Gunning Fog Score (GFS).
resultsDeepSeek V3 received a significantly higher total reviewer score compared to ChatGPT-4o (4 (IQR 1) vs. 3 (IQR 1); p = 0.016), and its responses contained more words on average (233 (IQR 113) vs. 139 (IQR 99), p = 0.004). While no significant difference was observed in FRES (-5.7 (IQR 17.5) vs. -10.1 (IQR 17.7), p = 0.140), both FKGL ( 16.5 (IQR 1.9) vs. 17.9 (IQR 2.7), p = 0.034) and GFS (18.8 (IQR 4.9) vs.20.6 (IQR 5.8), p = 0.016) scores were significantly lower for DeepSeek-V3, indicating superior readability.
conclusionWhile both ChatGPT-4o and DeepSeek-V3 generated fluent and readable responses, DeepSeek-V3 consistently provided longer, more comprehensive, and highly readable answers,accompanied by higher expert-rated accuracy to ED-related questions. These findings highlight the potential of newer AI models—driven by rapid competitive advancements—to effectively address patient inquiries in sensitive medical domains like ED.
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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.