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联影智能多项AI医疗解决方案展示应用成果
Zheng Quan Ri Bao· 2025-07-30 14:25
Core Viewpoint - Shanghai United Imaging Healthcare Co., Ltd. (United Imaging) showcased multiple AI medical solutions at the 2025 World Artificial Intelligence Conference, highlighting its collaboration with Sun Yat-sen University Cancer Prevention and Treatment Center since 2018 to develop smart diagnostic solutions in precision radiotherapy and artificial intelligence [2][3]. Group 1: AI Medical Solutions - United Imaging and Sun Yat-sen University have developed significant AI applications, including the brain metastasis AI system that automatically detects lesions and generates imaging reports, which are now implemented in over 400 hospitals nationwide [2]. - The collaboration has also led to the development of AI applications for bone metastasis, further enhancing diagnostic capabilities [2]. Group 2: Patient Interaction and Information Management - The partnership has created a smart diagnostic solution that enhances patient interaction through AI-driven pre-consultation processes, allowing patients to describe symptoms and upload previous examination reports via digital interfaces [3]. - An AI pre-consultation system utilizes structured semantic recognition technology to automatically input patient data into hospital systems, improving the efficiency of medical record generation and enhancing the overall patient experience [3]. Group 3: Precision Medicine and Data Utilization - In early 2024, the radiology department of Zhongshan Hospital and United Imaging identified chest CT scans as a key application area, targeting 73 types of chest abnormalities and collecting over 400,000 chest CT images for algorithm optimization [4]. - The collaboration resulted in the development of a unique chest multi-detection AI system capable of accurately diagnosing common chest abnormalities, positioning it as a leader in the industry [4]. - United Imaging's AI products are also making inroads into grassroots healthcare markets and international markets, promoting equitable healthcare solutions globally [4].
联影智能WAIC分论坛:医疗AI赋能肿瘤诊疗,智能体走进医疗多场景
IPO早知道· 2025-07-29 09:07
Core Viewpoint - Union Medical and AI technology is advancing in the healthcare sector, with a focus on enhancing diagnostic efficiency and accuracy through intelligent systems [2][12]. Group 1: AI Applications in Healthcare - Union Medical is collaborating with various medical institutions to develop intelligent systems for diagnosing multiple body parts, including the abdomen and brain [2][13]. - The AI application for cancer metastasis has been implemented in over 400 hospitals, indicating a significant expansion of its reach [3][5]. Group 2: Collaboration and Achievements - Since 2018, Union Medical has partnered with Sun Yat-sen University Cancer Center to develop important AI applications, including online adaptive radiotherapy and AI for metastatic tumors [4][5]. - The AI systems for brain and bone metastases have been successfully deployed nationwide, improving the efficiency and precision of cancer care [5][6]. Group 3: Enhancing Patient Experience - The collaboration has led to the creation of a smart consultation solution that streamlines patient information collection and reduces the burden of manual record-keeping for doctors [6][7]. - The AI pre-consultation system allows patients to describe their symptoms interactively and upload previous examination reports, enhancing the overall patient experience [6][7]. Group 4: Efficiency in Imaging Diagnosis - A human-machine collaboration challenge demonstrated that the chest multi-check AI system improved diagnostic efficiency by 25%, allowing for quicker identification of abnormalities [8][9]. - The chest multi-check AI system can automatically detect 73 common chest abnormalities with an average AUC value of 94%, showcasing its diagnostic accuracy [11][12]. Group 5: Future Developments - Union Medical plans to continue developing intelligent systems for various body parts in collaboration with medical institutions, aiming to provide stronger support for clinical diagnosis [13].