徐云程：以数据流通之活水，灌溉AI医疗创新之林

Core Insights - The integration of AI technology and high-quality, accessible medical data is becoming a core driving force for industry development, highlighting the complexity and value of data in the healthcare sector [1][2] - There exists a significant application gap between advanced AI technology demands and the current state of medical data systems, which are often isolated and difficult to access [1][2] Group 1: Challenges in Data Utilization - Medical data is scattered across various systems, often locked in non-communicating data silos, making it challenging for researchers and industry players to access necessary data for AI model training [1][2] - The need for a secure, trustworthy, and efficient environment for data flow and collaborative application is critical for advancing "AI + healthcare" initiatives [2] Group 2: Collaborative Infrastructure - Building a collaborative infrastructure requires participation from multiple stakeholders, including government agencies, healthcare institutions, technology companies, and biopharmaceutical firms, to establish trust mechanisms and standards for data sharing [2] - The Shanghai Modern Service Industry Association's Big Data Center aims to act as a connector and service provider within this complex collaborative network [2] Group 3: Future Outlook - The compilation of the "2025 AI + Healthcare Industry Application Map" is timely, providing a comprehensive overview of the industry landscape and identifying key nodes, achievements, and challenges within the "data-algorithm-scenario-value" chain [3] - The successful flow of medical data will empower AI technologies, leading to more precise diagnoses, efficient research, and broader health management solutions, necessitating patience, wisdom, and close collaboration among stakeholders [3]