OpenLens AI 自动完成医学信息学研究全流程，生成可发表的论文。
OpenLens AI: Fully Autonomous Research Agent for Health Infomatics
- 分模块代理协同工作，覆盖文献、数据分析到论文撰写
- 引入视觉语言反馈，能理解医学图像并保证结果可复现
- 适合医学研究者快速生成高质量论文，提升科研效率
医学信息学研究涉及多模态数据、知识快速更新，需融合生物医学、数据分析与临床实践。这类复杂性使其特别适合基于智能体的自动化方法。近年来，大语言模型驱动的智能体在文献综述、数据分析乃至端到端研究执行方面展现潜力。然而现有系统在医学可视化理解与领域特异性质量控制方面仍存在不足。为此，我们提出 OpenLens AI，一个专为医学信息学设计的全自动化框架。该框架集成文献调研、数据分析、代码生成与论文撰写等专用智能体，并通过视觉-语言反馈机制处理医学图像，结合可复现性质量控制。它可自动完成研究全流程，生成透明可追溯的出版级 LaTeX 论文，为医学信息学研究提供适配领域的自动化解决方案。
原文摘要 · Abstract (English)
Health informatics research is characterized by diverse data modalities, rapid knowledge expansion, and the need to integrate insights across biomedical science, data analytics, and clinical practice. These characteristics make it particularly well-suited for agent-based approaches that can automate knowledge exploration, manage complex workflows, and generate clinically meaningful outputs. Recent progress in large language model (LLM)-based agents has demonstrated promising capabilities in literature synthesis, data analysis, and even end-to-end research execution. However, existing systems remain limited for health informatics because they lack mechanisms to interpret medical visualizations and often overlook domain-specific quality requirements. To address these gaps, we introduce OpenLens AI, a fully automated framework tailored to health informatics. OpenLens AI integrates specialized agents for literature review, data analysis, code generation, and manuscript preparation, enhanced by vision-language feedback for medical visualization and quality control for reproducibility. The framework automates the entire research pipeline, producing publication-ready LaTeX manuscripts with transparent and traceable workflows, thereby offering a domain-adapted solution for advancing health informatics research.
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