用AI分析25年学术争论，揭示莱姆病研究范式转变
The Lyme Disease Controversy: An AI-Driven Discourse Analysis of a Quarter Century of Academic Debate and Divides
- 结合大模型与专家校验，系统分析数千篇文献
- 发现研究从感染论转向免疫机制解释
- 方法可复用于医学与社科领域争议分析
过去二十五年中，慢性莱姆病（CLD）与治疗后莱姆病综合征（PTLDS）的科学讨论演变为复杂且对立的争议，受研究重点变化、机构影响及不同解释模型驱动。本研究首次采用创新的混合式AI方法，结合大语言模型与结构化人工验证，对跨越25年的数千篇学术摘要进行大规模系统分析。通过将大语言模型（LLMs）与专家监督相结合，构建了量化追踪争议性医学领域知识演变的框架，适用于其他内容分析领域。分析显示，研究范式逐步由以感染为基础的模型，转向对持续症状的免疫介导解释。该研究为理解莱姆病研究中的结构性与认识论力量提供了新的实证视角，提出了一种可扩展、可复制的论述分析方法，并凸显了AI辅助方法在社会科学与医学研究中的价值。
原文摘要 · Abstract (English)
The scientific discourse surrounding Chronic Lyme Disease (CLD) and Post-Treatment Lyme Disease Syndrome (PTLDS) has evolved over the past twenty-five years into a complex and polarised debate, shaped by shifting research priorities, institutional influences, and competing explanatory models. This study presents the first large-scale, systematic examination of this discourse using an innovative hybrid AI-driven methodology, combining large language models with structured human validation to analyse thousands of scholarly abstracts spanning 25 years. By integrating Large Language Models (LLMs) with expert oversight, we developed a quantitative framework for tracking epistemic shifts in contested medical fields, with applications to other content analysis domains. Our analysis revealed a progressive transition from infection-based models of Lyme disease to immune-mediated explanations for persistent symptoms. This study offers new empirical insights into the structural and epistemic forces shaping Lyme disease research, providing a scalable and replicable methodology for analysing discourse, while underscoring the value of AI-assisted methodologies in social science and medical research.
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