[Efficacy and safety of artificial intelligence-based large language models for decision making support in herniology: evaluation by experts and general surgeons].

Objective: To evaluate the quality of recommendations provided by ChatGPT regarding inguinal hernia repair.

Material and methods: ChatGPT was asked 5 questions about surgical management of inguinal hernias. The chat-bot was assigned the role of expert in herniology and requested to search only specialized medical databases and provide information about references and evidence. Herniology experts and surgeons (non-experts) rated the quality of recommendations generated by ChatGPT using 4-point scale (from 0 to 3 points). Statistical correlations were explored between participants' ratings and their stance regarding artificial intelligence.

Results: Experts scored the quality of ChatGPT responses lower than non-experts (2 (1-2) vs. 2 (2-3), p<0.001). The chat-bot failed to provide valid references and actual evidence, as well as falsified half of references. Respondents were optimistic about the future of neural networks for clinical decision-making support. Most of them were against restricting their use in healthcare.

Conclusion: We would not recommend non-specialized large language models as a single or primary source of information for clinical decision making or virtual searching assistant.