Core Viewpoint - The article discusses the development of DeepRare, an AI system designed to improve the diagnosis of rare diseases, which currently face long diagnosis times and high misdiagnosis rates. The system outperforms experienced specialists by simulating human expert "slow thinking" logic [1][4]. Group 1: Clinical Need for AI - The current medical knowledge explosion makes it impossible for even the most talented doctors to keep up with over 7,000 rare diseases, leading to significant delays in diagnosis and treatment [6]. - The integration of AI in rare disease diagnosis is seen as a necessary step to alleviate the burden on healthcare professionals and improve patient outcomes, especially in pediatric and genetic cases [6]. Group 2: Technological Leap - DeepRare represents a paradigm shift from traditional predictive models to a system that emphasizes logical reasoning and decision-making, allowing it to autonomously plan diagnostic paths rather than merely recalling information [9]. - The system incorporates a "dynamic reflection mechanism" that identifies logical gaps in patient data and actively seeks new evidence, enhancing its diagnostic accuracy [10]. Group 3: Implementation and Productization - The establishment of OneX Intelligence aims to bridge the gap between academic research and practical application, transforming DeepRare into a clinical decision support system that integrates seamlessly with existing hospital systems [13]. - DeepRare has been deployed within Xinhua Hospital for internal testing, focusing on quality control in rare disease diagnosis and enhancing the interpretation of genetic sequencing reports through automation [14]. Group 4: Organizational Innovation - The collaborative model at Shanghai Jiao Tong University promotes deep integration between AI researchers and medical professionals, facilitating a more effective development process for AI applications in healthcare [18]. - The success of DeepRare is viewed as a reflection of the innovative organizational structure that encourages not only academic publication but also the commercialization of research findings [19].