21对话｜联影智能首席科学家高耀宗：人机协同是AI医疗最优解

Core Viewpoint - Geoffrey Hinton, a prominent figure in AI, has shifted from warning about AI risks to expressing optimism about its applications, particularly in medical imaging, where AI can outperform human doctors in information retrieval and risk assessment [1] Company Overview - United Imaging Healthcare established a subsidiary, United Imaging Intelligence, in 2017 to focus on AI medical solutions, leading to the launch of over 100 AI applications, with 15 approved by NMPA, 15 by FDA, and 31 by EU CE, making it a leader in global medical AI certifications [1] - The company has developed a comprehensive ecosystem combining imaging devices and AI technology, which is attractive for the medical AI market in China [3][19] Key Personnel - Gao Yaozong, the Chief Scientist and Senior Vice President of United Imaging Intelligence, has a background in computer vision and AI, previously working at Apple before returning to China to contribute to the medical AI sector [2][19] Market Dynamics - The Chinese medical imaging market is undergoing transformation due to AI, which is enhancing disease screening, diagnosis, risk assessment, and clinical decision-making [1] - The vast population and diverse disease spectrum in China provide a rich data environment for training AI models, making it an ideal location for medical AI development [19] AI Applications in Healthcare - AI-assisted diagnosis is becoming a common tool for radiologists, significantly reducing the rate of missed diagnoses by serving as a "second pair of eyes" [3] - United Imaging has developed a lung nodule diagnosis grading system, C-Lung-RADS, based on 120,000 cases of Chinese population data, improving early lung cancer screening accuracy [4] Technological Innovations - The company employs a dual-path strategy of using both open-source models and proprietary development to enhance AI capabilities in medical imaging [6] - During the COVID-19 pandemic, the company rapidly developed AI systems for diagnostic support, demonstrating strong technical responsiveness [8] Future Directions - The ideal future technology path involves combining the strengths of general large models and specialized small models to enhance disease recognition and ensure precision in critical tasks [15] - The company aims to make AI a supportive tool for doctors, automating routine tasks and providing diagnostic suggestions, while addressing ethical and responsibility issues for higher autonomy in AI [16] Collaboration and Data Management - United Imaging collaborates with hospitals to gather data while ensuring patient privacy and data security, employing a "data does not leave the hospital" approach for model training [9] - The company focuses on multi-center validation to ensure the generalizability of AI models across different hospitals [10] Regulatory Environment - AI medical products are classified as high-risk and require stringent regulatory approval, with over 100 AI products already approved in China [14] - The company actively participates in shaping regulatory guidelines and industry standards to facilitate the development of AI in healthcare [14]