Table_1_Potential application of ChatGPT in Helicobacter pylori disease relevant queries.XLSX

BackgroundAdvances in artificial intelligence are gradually transforming various fields, but its applicability among ordinary people is unknown. This study aims to explore the ability of a large language model to address Helicobacter pylori related questions.
MethodsWe created several prompts on the basis of guidelines and the clinical concerns of patients. The capacity of ChatGPT on Helicobacter pylori queries was evaluated by experts. Ordinary people assessed the applicability.
ResultsThe responses to each prompt in ChatGPT-4 were good in terms of response length and repeatability. There was good agreement in each dimension (Fleiss’ kappa ranged from 0.302 to 0.690, p < 0.05). The accuracy, completeness, usefulness, comprehension and satisfaction scores of the experts were generally high. Rated usefulness and comprehension among ordinary people were significantly lower than expert, while medical students gave a relatively positive evaluation.
ConclusionChatGPT-4 performs well in resolving Helicobacter pylori related questions. Large language models may become an excellent tool for medical students in the future, but still requires further research and validation.

背景：人工智能技术的进步正逐步重塑诸多行业领域，但其在普通大众中的适用性仍未明确。本研究旨在探究大语言模型（Large Language Model，LLM）针对幽门螺杆菌相关问题的处理能力。
方法：本研究依据临床指南与患者的临床关切点构建了多组提示词（prompt）。邀请专家对ChatGPT处理幽门螺杆菌相关查询的能力进行评估，同时由普通大众对其适用性进行评价。
结果：ChatGPT-4针对各提示词的回复在篇幅与重复性上均表现优异。各维度均具有良好的一致性，Fleiss’ Kappa值区间为0.302至0.690，p<0.05。专家评分中的准确性、完整性、实用性、理解性与满意度得分普遍较高。普通大众对实用性与理解性的评分显著低于专家，而医学生的评价则相对积极。
结论：ChatGPT-4在处理幽门螺杆菌相关问题上表现出色。大语言模型未来有望成为医学生的优质辅助工具，但仍需开展进一步研究与验证。