Core Insights - The forum focused on the inclusive path of medical AI and the construction of a global health ecosystem, featuring key figures from various sectors including medicine, research, and investment [1] - The collaboration between Sun Yat-sen University Cancer Center and United Imaging since 2018 has led to significant advancements in AI applications for cancer treatment, including online adaptive radiotherapy and AI for metastatic tumors [1][2] Group 1: AI Applications in Oncology - The AI applications for detecting brain and bone metastases have been implemented in over 400 hospitals nationwide, enhancing the efficiency and precision of cancer care for more patients [2] - A practical test demonstrated that AI-assisted doctors completed image diagnosis and report writing 25% faster than those without AI support, showcasing the technology's effectiveness in complex cases [2][3] Group 2: Impact on Grassroots Healthcare - The collaboration between United Imaging and Shache County People's Hospital has led to the development of an AI for rapid detection of suspected tuberculosis, improving screening efficiency and accessibility for local residents [3] - The integration of AI technology into healthcare systems is part of a broader initiative supported by national policies aimed at enhancing medical capabilities in rural areas [3]

Group 1 - The core viewpoint of the articles highlights the significant advancements in AI technology within the medical field, particularly in imaging diagnostics and patient interactions, showcasing the efficiency and accuracy improvements brought by AI [1][5][6] - A demonstration at the 2025 WAIC showed that AI-assisted teams completed imaging diagnostics and report writing 25% faster than teams relying solely on human expertise [1] - The collaboration between Zhongshan Hospital and AI companies has led to the development of AI applications for detecting brain and bone metastases, which are now implemented in over 400 hospitals nationwide, enhancing patient care [2] Group 2 - Traditional patient visits often involve cumbersome processes, such as carrying paper medical histories, which can lead to repeated tests and increased costs; AI solutions aim to streamline these processes [3][4] - The development of an electronic medical record AI system allows for real-time transcription of doctor-patient conversations, improving the accuracy and completeness of medical records [4] - The introduction of a chest CT AI system capable of detecting 73 types of abnormalities has achieved an average AUC value of 94%, indicating high diagnostic accuracy [7] Group 3 - AI technology is being integrated into healthcare in remote areas, such as Xinjiang, to enhance the efficiency of tuberculosis screening, addressing the challenges posed by limited medical resources [9] - The international response to Chinese medical AI technology has been positive, with reports from Indonesia highlighting successful case studies where AI identified conditions that local doctors missed, demonstrating the potential for AI to improve healthcare access globally [10][11]