用自动化分析中国医疗器械软件监管数据，揭示AI应用趋势。
Data-Driven Analysis of AI in Medical Device Software in China: Trends of Deep Learning and Traditional AI Based on Regulatory Data
- 从400万条数据中自动提取2174个医疗器械软件注册信息。
- 发现呼吸、眼科/内分泌、骨科是AI应用最集中的三大领域。
- 为监管机构和研究者提供可复现的AI医疗设备分析方法。
人工智能在医疗器械软件（MDSW）中代表了一种变革性临床技术，受到医学界与监管机构日益关注。本研究采用数据驱动方法，从国家药品监督管理局（NMPA）监管数据库中自动提取并分析人工智能医疗器械（AIMD）。随着公开监管数据持续增长，需具备可扩展的分析方法。自动化筛查监管信息对生成可复现的洞察至关重要，可快速适应不断变化的医疗器械环境。共评估超过400万条记录，识别出2,174个MDSW注册，包括531个独立应用和1,643个集成于医疗器械中的产品，其中43个为AI-enabled。结果显示，使用AIMD领先的医学专科依次为呼吸（20.5%）、眼科/内分泌（12.8%）和骨科（10.3%）。该方法显著提升数据提取速度，增强了对比分析能力。本研究首次对中国范围内的AIMD进行了广泛、数据驱动的探索，展示了自动化监管数据分析在理解与推动AI医疗技术发展方面的潜力。
原文摘要 · Abstract (English)
Artificial intelligence (AI) in medical device software (MDSW) represents a transformative clinical technology, attracting increasing attention within both the medical community and the regulators. In this study, we leverage a data-driven approach to automatically extract and analyze AI-enabled medical devices (AIMD) from the National Medical Products Administration (NMPA) regulatory database. The continued increase in publicly available regulatory data requires scalable methods for analysis. Automation of regulatory information screening is essential to create reproducible insights that can be quickly updated in an ever changing medical device landscape. More than 4 million entries were assessed, identifying 2,174 MDSW registrations, including 531 standalone applications and 1,643 integrated within medical devices, of which 43 were AI-enabled. It was shown that the leading medical specialties utilizing AIMD include respiratory (20.5%), ophthalmology/endocrinology (12.8%), and orthopedics (10.3%). This approach greatly improves the speed of data extracting providing a greater ability to compare and contrast. This study provides the first extensive, data-driven exploration of AIMD in China, showcasing the potential of automated regulatory data analysis in understanding and advancing the landscape of AI in medical technology.
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