Core Insights - The rapid integration of AI technology into the healthcare sector is transforming traditional medical practices, particularly in areas such as imaging, diagnostics, drug development, and health management [1][12] - The Chinese AI+ healthcare market is projected to grow from 31.5 billion yuan in 2023 to over 80 billion yuan by 2025, with a compound annual growth rate of 58.3% [1] - The global AI healthcare market is expected to exceed $1.5 trillion by 2030, with drug development, imaging diagnostics, and health management accounting for over 60% of this growth [1] AI in Pathology - Pathology diagnosis is considered the "gold standard" for disease diagnosis, especially for cancer, but the traditional process is time-consuming and requires high levels of expertise [2] - There is a significant shortage of pathologists in China, leading to unequal distribution of medical resources and increased patient costs [2] RuiPath Model Development - The RuiPath model, developed by Ruijin Hospital in collaboration with Huawei, is a clinical-grade multi-modal pathology model that covers 90% of cancer cases in China and includes over a hundred auxiliary diagnostic tasks [3] - The open-sourced RuiPath model includes a visual foundation model, a multi-cancer test dataset, and a complete practical guide, significantly lowering the barriers for grassroots hospitals to implement AI-assisted diagnostics [4] Global Collaboration and Standardization - Ruijin Hospital has initiated a global multi-center plan to promote the RuiPath model, focusing on improving diagnostic capabilities in resource-poor areas [5] - The collaboration aims to standardize diagnostic results across different centers and enhance the performance and applicability of the RuiPath model [5] Transition to Smart Pathology - The partnership between Huawei and Ruijin Hospital has evolved through clear phases of digitalization and smart pathology, culminating in the development of a large model capable of precise cancer identification [6] - The introduction of Huawei's ModelEngine AI toolchain has transformed the workflow of pathologists, increasing efficiency and reducing the time required for AI application deployment [7][8] Future Implications - The open-sourcing of the RuiPath model is expected to improve pathology diagnosis in grassroots hospitals, alleviating the imbalance in medical resource distribution [12] - Long-term, this collaboration is anticipated to attract more healthcare institutions and tech companies to participate in the development and application of medical AI, enhancing early diagnosis, personalized treatment, and drug development [12][14]

Core Viewpoint - The article highlights the significant advancement of the RuiPath pathology model, marking a transition from technological breakthroughs to ecological sharing in the field of domestic medical AI [2][4]. Group 1: RuiPath Pathology Model Development - The RuiPath pathology model, developed by Ruijin Hospital with support from Huawei, has progressed through two stages: "digitalization" and "intelligence" [2][11]. - The core visual foundation model of RuiPath has been open-sourced, utilizing over one million high-quality digital pathology slice data, and is supported by Huawei's AI toolchain, ModelEngine [4][11]. - The model covers seven common cancer types, including lung cancer and breast cancer, and provides testing datasets and practical guidelines for downstream tasks [4][6]. Group 2: Global Multi-Center Plan - On June 30, Ruijin Hospital, along with 12 domestic and international medical institutions, launched a global multi-center plan for the RuiPath pathology model to facilitate continuous iteration [5]. - The plan aims to enhance accessibility, promote standardization, and foster technological innovation in pathology diagnostics [6]. Group 3: Huawei's Initiatives - Huawei proposed four key initiatives to accelerate the implementation of AI in the medical sector, including standardizing and managing medical datasets, building a shared intelligent diagnostic data infrastructure, and promoting the standardization of data engineering and model engineering [8][9]. - The collaboration between Huawei and Ruijin Hospital serves as a significant case study, demonstrating the transition from digital pathology to intelligent pathology, with a focus on high-quality data accumulation [11][13].