构建开放可查的医学影像AI模型库，助力研究复现与临床转化。
OpenRad: a Curated Repository of Open-access AI models for Radiology
- 基于大模型自动提取文献信息，人工审核确保数据准确。
- 收录1700个模型，覆盖所有影像模态和放射亚专科。
- 支持关键词搜索与多维度筛选，适合研究人员与临床医生使用。
人工智能在医学影像领域的快速发展产生了大量分散于不同平台的模型，限制了其可发现性、可复现性和临床应用。为此，我们创建了OpenRad——一个经筛选、标准化且开源的医学影像AI模型仓库，整合了包括预训练权重和交互式应用在内的详细信息。通过对截至2025年12月的PubMed、arXiv和Scopus中5239篇同行评审论文及预印本进行回顾性分析，采用本地部署的大语言模型（gpt-oss:120b）依据RSNA AI Roadmap JSON模式生成模型记录，并由十位专家审核。在225篇随机抽样论文上评估了大模型输出稳定性，结构化字段的莱文斯坦相似度超过90%。最终纳入1694篇论文，涵盖所有影像模态（CT、MRI、X光、超声）和放射学亚专科。自动化提取结果稳定，80.5%的记录修改被定为轻微。统计分析显示卷积神经网络和变压器架构占主导地位，而磁共振成像在神经放射学模型中占比最高（621个）。研究产出主要集中于中国和美国。OpenRad网页界面支持按模态、亚专科、用途、验证状态和演示可用性等条件筛选，具备实时统计数据。社区可通过专用门户提交新模型。OpenRad目前包含约1700个开放获取、经筛选的医学影像AI模型，配备标准化元数据，并补充代码仓库分析，形成全面、可检索的资源，服务于整个放射学领域。
原文摘要 · Abstract (English)
The rapid developments in artificial intelligence (AI) research in radiology have produced numerous models that are scattered across various platforms and sources, limiting discoverability, reproducibility and clinical translation. Herein, OpenRad was created, a curated, standardized, open-access repository that aggregates radiology AI models and providing details such as the availability of pretrained weights and interactive applications. Retrospective analysis of peer reviewed literature and preprints indexed in PubMed, arXiv and Scopus was performed until Dec 2025 (n = 5239 records). Model records were generated using a locally hosted LLM (gpt-oss:120b), based on the RSNA AI Roadmap JSON schema, and manually verified by ten expert reviewers. Stability of LLM outputs was assessed on 225 randomly selected papers using text similarity metrics. A total of 1694 articles were included after review. Included models span all imaging modalities (CT, MRI, X-ray, US) and radiology subspecialties. Automated extraction demonstrated high stability for structured fields (Levenshtein ratio > 90%), with 78.5% of record edits being characterized as minor during expert review. Statistical analysis of the repository revealed CNN and transformer architectures as dominant, while MRI was the most commonly used modality (in 621 neuroradiology AI models). Research output was mostly concentrated in China and the United States. The OpenRad web interface enables model discovery via keyword search and filters for modality, subspecialty, intended use, verification status and demo availability, alongside live statistics. The community can contribute new models through a dedicated portal. OpenRad contains approx. 1700 open access, curated radiology AI models with standardized metadata, supplemented with analysis of code repositories, thereby creating a comprehensive, searchable resource for the radiology community.
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