Core Viewpoint - The RuiPath pathology model, developed by Ruijin Hospital in collaboration with Huawei, aims to enhance the efficiency and accuracy of pathology diagnostics in China by leveraging AI technology [1][5]. Group 1: Model Development and Features - The RuiPath model is a clinical-grade multimodal pathology model that covers 90% of the annual cancer incidence in China, addressing 19 common cancer types and hundreds of auxiliary diagnostic tasks [1][5]. - The model has achieved state-of-the-art (SOTA) performance in 7 out of 14 auxiliary diagnostic tasks tested against 12 mainstream public datasets, surpassing the performance of Harvard's UNI2 model [4]. - The model's core "visual foundation model" was developed using over one million high-quality digital pathology slides from Ruijin Hospital, utilizing Huawei's AI toolchain for annotation, training, and fine-tuning [2][4]. Group 2: Efficiency and Impact - The implementation of the RuiPath model allows pathologists to increase their daily workload from 200-300 slides to 400-500 or more, significantly improving diagnostic efficiency [5]. - The model aims to standardize digital pathology practices across hospitals in China, enabling easier deployment and reducing training costs for other institutions [5][10]. - The collaboration between Ruijin Hospital and Huawei has streamlined the model training process, allowing for the completion of the RuiPath model development with only a 16-card cluster, making it more accessible for hospitals [10][11]. Group 3: Industry Challenges and Solutions - There is a significant shortage of pathology doctors in China, with only about 20,000 available and a gap of 140,000 needed, highlighting the importance of AI solutions in addressing this challenge [5]. - The partnership has evolved through two phases: digitalization and smart pathology, focusing on data standardization and collaborative model development [7][8]. - The use of Huawei's ModelEngine has transformed the annotation process, allowing pathologists to review over 700 slides in a day, thus enhancing both efficiency and accuracy [10].

在病理人工智能落地过程中仍面临数据、算法、算力、存力四方面挑战 病理诊断是绝大部分疾病，尤其是肿瘤疾病的诊断"金标准"，是医生的医生。病理诊断耗时长，再加上 我国病理医生缺口大，病理医生分布不均，如何用AI在提高医生工作效率的同时，又可以降低漏诊、 误诊的风险，成为医疗行业关注的焦点。 6月30日，瑞金医院联合华为宣布开源RuiPath病理模型，意在医院降低病理AI辅助诊断部署门槛，这也 成为上海医疗机构首个开源的病理模型。 此次开源的为RuiPath病理模型的核心"视觉基础模型"。根据官方介绍，该模型依托瑞金医院百万张高 质量数字病理切片数据，基于华为AI全流程工具链ModelEngine进行标注、训练和模型精调而成，在业 界12个主流公开数据集的14个辅助诊断任务测试中，有7个达到业界领先水平（SOTA），并已具备临 床验证能力。本次开源配套提供测试数据集，覆盖了肺癌、结直肠癌、甲状腺癌、胃癌、乳腺癌、前列 腺癌、胰腺癌等7个常见癌种。 中国工程院院士、瑞金医院院长宁光在现场表示，病理大模型只有真正临床应用才能产生价值实现AI 普惠。 病理诊断指通过手术切除、内镜活检、细针穿刺等方式获取人体组织或细胞，借 ...