Angyal Viola, Bertalan Ádám, Domján Péter, Dinya Elek
Semmelweis University Doctoral College, Health Sciences Division, Institute of Digital Health Sciences, Budapest, Hungary.
Semmelweis University, Doctoral College, Health Sciences Division Interdisciplinary Applied Health Sciences Program, Budapest, Hungary.
BMC Med Inform Decis Mak. 2025 Jul 1;25(1):242. doi: 10.1186/s12911-025-03088-3.
The rapid advancement of artificial intelligence, driven by Generative Pre-trained Transformers (GPT), has transformed natural language processing. Prompt engineering plays a key role in guiding model outputs effectively. Our primary objective was to explore the possibilities and limitations of a custom GPT, developed via prompt engineering, as a patient education tool, which delivers publicly available information through a user-friendly design that facilitates more effective access to cervical cancer screening knowledge.
The system was developed using the OpenAI GPT-4 model and Python programming language, with the interface built on Streamlit for cloud-based accessibility and testing. It initially presented questions to testers for preliminary assessment. For cervical cancer-related information, we referenced medical guidelines. Iterative testing optimized the prompts for quality and relevance; techniques like context provision, question chaining, and prompt-based constraints were used. Human-in-the-loop and two independent medical doctor evaluations were employed. Additionally, system performance metrics were measured.
The web application was tested 115 times over a three-week period in 2024, with 87 female (76%) and 28 male (24%) participants. A total of 112 users completed the user experience questionnaire. Statistical analysis showed a significant association between age and perceived personalization (p = 0.047) and between gender and system customization (p = 0.037). Younger participants reported higher engagement, though not significantly. Females valued guidance on screening schedules and early detection, while males highlighted the usefulness of information regarding HPV vaccination and its role in preventing HPV-related cancers. Independent evaluations by medical doctors demonstrated consistent assessments of the system's responses in terms of accuracy, clarity, and usefulness.
While the system demonstrates potential to enhance public health awareness and promote preventive behaviors, encouraging individuals to seek information on cervical cancer screening and HPV vaccination, its conversational capabilities remain constrained by the inherent limitations of current language model technology.
Although custom GPTs can not substitute a healthcare consultations, these tools can streamline workflows, expedite information access, and support personalized care. Further research should focus on conducting well-designed randomized controlled trials to establish definitive conclusions regarding its impact and reliability.
Not applicable.
在生成式预训练变换器（GPT）的推动下，人工智能的迅速发展改变了自然语言处理。提示工程在有效引导模型输出方面起着关键作用。我们的主要目标是探索通过提示工程开发的定制GPT作为患者教育工具的可能性和局限性，该工具通过用户友好的设计提供公开可用的信息，便于更有效地获取宫颈癌筛查知识。
该系统使用OpenAI GPT-4模型和Python编程语言开发，界面基于Streamlit构建，以便于基于云的访问和测试。它最初向测试人员提出问题进行初步评估。对于宫颈癌相关信息，我们参考了医学指南。迭代测试优化了提示的质量和相关性；使用了提供上下文、问题链接和基于提示的约束等技术。采用了人工参与和两名独立医生评估。此外，还测量了系统性能指标。
该网络应用程序在2024年的三周内进行了115次测试，有87名女性（76%）和28名男性（24%）参与者。共有112名用户完成了用户体验问卷。统计分析显示年龄与感知个性化之间存在显著关联（p = 0.047），性别与系统定制之间存在显著关联（p = 0.037）。年轻参与者报告的参与度更高，尽管不显著。女性重视筛查时间表和早期检测方面的指导，而男性则强调HPV疫苗接种信息及其在预防HPV相关癌症中的作用的有用性。医生的独立评估表明，对系统回答的准确性、清晰度和有用性进行了一致评估。
虽然该系统显示出增强公众健康意识和促进预防行为的潜力，鼓励个人寻求宫颈癌筛查和HPV疫苗接种信息，但其对话能力仍然受到当前语言模型技术固有局限性的限制。
虽然定制GPT不能替代医疗咨询，但这些工具可以简化工作流程、加快信息获取并支持个性化护理。进一步的研究应侧重于进行精心设计的随机对照试验，以确定其影响和可靠性的确切结论。
不适用。
