Performance of next-generation AI chatbots in gynecological knowledge assessment: a comparative pilot study of ChatGPT-5, Gemini-3, DeepSeek-V3.2, and Claude-4.5-Opus

Under constrained non-reasoning prompts, even next-generation AI chatbots demonstrate unsatisfactory performance in gynecology. The qualitative analysis suggests that models often rely on probabilistic keyword matching rather than physiological simulation, leading to theoretically dangerous clinical errors (e.g., misdiagnosing adrenal enzymes). While potential exists, current reliability is insufficient for unsupervised use in gynecological education. These findings highlight the critical need for "chain-of-thought" prompting and human expert oversight.