"最后一公里"畅通与否，关乎人工智能技术能否在基层落地生根，最终能否让优质医疗资源突破时空壁 垒，切实缓解"看病难、看病贵"的民生关切。当前，加速构建的紧密型县域医共体智慧云平台，正是打 通这一堵点的核心枢纽。这条以省县联动、多级协同为支撑的智慧"高速路"，高效贯通上级医院的专 家、技术与数据资源，助力AI影像诊断、远程会诊等智能服务精准下沉基层，使优质医疗服务便捷可 及、"家门口"可享，显著提升了健康服务的公平性与可及性。 【专家点评】 作者：梅浩（工业和信息化部网络空间公共安全研究中心特约研究员） 以大模型为代表的新一代人工智能技术，深度赋能医疗健康领域，在医学影像判读、疾病风险预警、辅 助诊疗决策等领域展现出巨大潜力和应用价值，有力助推临床诊疗模式优化升级，为解决医疗资源分布 不均难题、推动优质医疗资源扩容下沉注入新动能。深化人工智能在医疗健康领域的融合应用，打通 AI医疗落地应用的"最后一公里"，是让技术创新红利真正惠及亿万民众健康福祉的关键所在。 推动AI深度融入临床实践与基层健康服务体系。坚决摒弃"技术空转"，牢固树立以临床需求为导向的研 发应用理念。聚焦"最后一公里"攻坚，将AI技术部署深度嵌入 ...

Core Insights - The article highlights the increasing importance of high-quality data in the biopharmaceutical industry, especially following the NIH's ban on certain researchers accessing critical biological databases, emphasizing that data is now a core strategic resource [1] - The establishment of the National Data Bureau in China marks a significant step in promoting data governance and the integration of medical data as a valuable resource for innovation and efficiency in healthcare [2] Group 1: Data Governance and Integration - The strategic position of data has been elevated at the national level, with data now recognized as a key production factor alongside traditional elements like land and labor [2] - The Shanghai city has initiated the "Shanghai Urban Trusted Data Space" project, attracting nearly 300 companies and developing over 300 data products, showcasing the active efforts in building a trusted data ecosystem [2] - Medical data is transitioning from being a byproduct of patient treatment to a powerful driver for medical innovation and resource optimization [3] Group 2: Real-World Data and Drug Development - The construction of a big data platform for late-stage pancreatic cancer has gathered data from 100,000 patients across 31 provinces, providing a solid foundation for precision treatment [5] - Real-world evidence (RWE) is becoming crucial in drug development, allowing for faster and more efficient research processes compared to traditional clinical trials [6][7] - The use of historical real-world data can significantly reduce the time required for drug approval, enabling quicker access to new treatments for patients [7] Group 3: Challenges and Innovations - Despite the abundance of real-world data in China, the quality of this data varies, presenting challenges for effective data governance and utilization [7] - The issue of "data silos" and the need for improved communication between data providers and users are highlighted as significant barriers to achieving effective data flow [8][10] - Innovations such as the MDT intelligent system developed by Roche and local hospitals aim to enhance data structuring and extraction efficiency, paving the way for more insightful clinical practices [9]