但需要看到的是，订单出现，并不等同于商业模式完全成熟。当前阶段，医疗AI最清晰的付费方仍然 是政府与公立医疗体系，其核心逻辑是公共投入与能力建设，而非市场化回报。这也决定了，真正跑通 的不是"爆款产品模式"，而是"基础设施模式"。 同时，在C端与市场化层面，医疗AI仍处于"慢变量"阶段。无论是面向用户的健康管理智能体，还是面 向医生的辅助决策工具，其商业价值更多体现在降低系统成本、提升服务效率，而非直接创造新增收 入。 深圳商报首席记者 袁静娴 如果说前两年医疗AI更多停留在"验证价值"的阶段，那么2025年底，一个新的变化开始显现——真正 的"买单方"出现了，而且出手不凡。 据公开报道，过去一个月内，科大讯飞、支付宝、百度先后中标上亿元级别的政府医疗项目。三笔订 单，指向的并非单一医院或具体应用，而是医疗AI的底层平台与基础能力建设。 这一变化意味着，医疗AI的商业化，正在从"医院试点买单"走向"体系级采购"。 上亿订单的出现，更像是医疗AI商业化的"第一道闸门"被打开"。当AI从"平台建设期"进入"深度使用 期"，其能否在真实医疗场景中持续创造可衡量的价值，才是决定这一赛道最终格局的关键。 ...

Core Viewpoint - The article discusses the launch of the GAPS (Grounding, Adequacy, Perturbation, Safety) evaluation framework for assessing the clinical capabilities of AI models in the medical field, specifically focusing on lung cancer [1][2][10]. Group 1: GAPS Framework Overview - GAPS is the world's first evaluation framework for AI clinical capabilities, developed in collaboration with a team of thoracic surgeons and led by Professor Wang Jun from Peking University People's Hospital [1][4]. - The framework addresses the limitations of existing medical AI assessments, which often rely on exam-style questions and lack comprehensive evaluation of clinical depth, integrity, robustness, and safety [2][7][10]. - GAPS includes a fully automated evaluation toolchain that generates questions, scoring criteria, and multi-dimensional scoring, focusing on 92 questions covering 1691 clinical points in lung cancer [2][18]. Group 2: Evaluation Dimensions - GAPS breaks down clinical competence into four orthogonal dimensions: 1. Grounding (G): Depth of understanding beyond mere facts, requiring reasoning and decision-making [11]. 2. Adequacy (A): Completeness of responses, with a three-tier evaluation system for essential, conditional, and additional recommendations [12][31]. 3. Perturbation (P): Robustness against real-world uncertainties, tested through various perturbation scenarios [13][34]. 4. Safety (S): Establishing a risk framework to ensure that medical AI does not produce harmful recommendations, with a strict penalty for catastrophic errors [16][36]. Group 3: Technological Innovations - GAPS features an end-to-end automated evaluation pipeline that generates high-quality assessment sets based on clinical guidelines, allowing for rapid expansion into other medical specialties [17][19]. - The framework utilizes advanced techniques such as evidence-based knowledge graphs and virtual patient generation to ensure that each question is grounded in reliable clinical evidence [20][23]. Group 4: Performance Insights - Initial evaluations of leading AI models using GAPS revealed significant performance gaps, particularly in handling uncertainty and providing comprehensive clinical recommendations [29][31]. - The results indicated that while models excelled in factual recall, they struggled with complex decision-making and reasoning under uncertainty, highlighting the need for further development in AI clinical capabilities [29][30]. Group 5: Future Implications - The introduction of GAPS marks a paradigm shift in medical AI evaluation from mere exam scores to assessing clinical competence, emphasizing the importance of evidence-grounded reasoning and uncertainty management in future AI developments [39][40].

Core Viewpoint - The article discusses the challenges and opportunities in the medical AI sector, particularly focusing on the company Yunzhisheng, which has established itself as a leading player in the field by successfully integrating AI solutions into hospitals and demonstrating significant operational efficiency improvements [1][9][64]. Group 1: Medical AI Challenges - Patients increasingly consult AI chatbots before visiting doctors, leading to communication challenges in clinical settings [2][3]. - The high "hallucination rate" of general AI models in medical contexts can reach up to 40%, raising concerns about their reliability [4][5]. - Medical AI must navigate stringent requirements for stability, acceptance across various healthcare systems, and the high costs associated with medical errors [12][18][19]. Group 2: Yunzhisheng's Position - Approximately 40% of top-tier hospitals in China have adopted Yunzhisheng's medical AI solutions, indicating its strong market presence [9][22]. - The company has deployed its solutions in 400 hospitals, with a nearly 90% direct usage rate of generated medical records, significantly reducing doctors' time spent on documentation [22][23][25]. - Yunzhisheng's medical AI solutions are designed to integrate seamlessly into existing workflows, enhancing efficiency without adding to the workload of healthcare professionals [58][60]. Group 3: Technological Advancements - Yunzhisheng's latest model, "Shanhai·Zhimed 5.0," employs a dual-core system capable of processing structured information and multimodal inputs, enhancing its diagnostic capabilities [34][36]. - The model's architecture includes a three-layer data paradigm that improves its understanding of medical contexts and reduces hallucination rates to below 3% [42]. - The company has consistently ranked at the top of medical AI evaluation platforms, demonstrating its technological superiority [45][46]. Group 4: Business Growth and Market Trends - Yunzhisheng's medical business revenue reached 0.70 billion, a 22.3% increase year-on-year, highlighting its growth trajectory [66]. - The average revenue per medical client has more than doubled, indicating a significant increase in customer value [66]. - The broader market for medical AI is expected to grow, with increasing investments and policy support aimed at integrating AI into healthcare workflows [79][82][86].

2025年12月，在上海人工智能研究院打造的国内权威中文医疗大模型评测体系MedBench 4.0中，公司在 医疗智能体、大语言模型和多模态大模型中分别取得94.6分、65.7分、 59.6分的优异成绩，一举包揽了 医疗大模型全部三项技术範式第一，用实力打造行业标杆。而在国家人工智能应用中试基地(医疗)?浙 江发布的《MedAIBench测评榜(优秀国产医疗大模型)》中，公司医疗大模型凭借扎实的技术积累荣耀 登榜，彰显AI医疗垂域硬核实力。 智通财经APP讯，云知声(09678)发布公告，近日，公司发布医疗领域专家大模型"山海?知医大模型 5.0"版本("医疗大模型")，构建"医学文本大模型+医学多模态大模型"双核心产品体系，全面覆盖文本处 理、智能体协同、多模态感知等核心能力，整合医学知识问答、临床任务规划、影像解析等多元功能， 形成当前业界能力维度最丰富的医疗AI技术支撑体系之一。医疗大模型能够深度模拟临床思维进行复 杂推理，实现精准鉴别诊断与循证决策。公司依托海量优质医疗数据与专属知识库训练，在医学知识问 答、信息抽取等核心任务中达到业界顶尖水平;通过持续课程学习、知识图谱增强及循证对齐训练，最 大限度 ...

Core Insights - The company has launched the "Shanhai·Zhi Medical Model 5.0," a dual-core product system in the medical field, integrating a medical text model and a medical multimodal model, which covers core capabilities such as text processing, intelligent agent collaboration, and multimodal perception [1] - The medical model is designed to deeply simulate clinical thinking for complex reasoning, achieving precise diagnostic differentiation and evidence-based decision-making [1] Performance Metrics - In the MedBench 4.0 evaluation system, the company achieved scores of 94.6, 65.7, and 59.6 in medical intelligent agents, large language models, and multimodal models respectively, securing the top position in all three technical paradigms [2] - The company's medical model has been recognized in the MedAIBench evaluation list for excellent domestic medical models, showcasing its robust technical foundation [2] Application and Industry Impact - The medical model has been successfully implemented in numerous top-tier hospitals, demonstrating its clinical practical value and adaptability to industry standards and clinical needs [2] - The collaboration with top-tier hospitals for technical validation in high-demand clinical auxiliary diagnosis scenarios highlights the model's alignment with real-world medical requirements [2]

Core Insights - The company has launched the "Shan Hai Zhi Yi Model 5.0," a medical expert large model that integrates a dual-core product system of "medical text large model + medical multimodal large model," covering essential capabilities such as text processing, intelligent agent collaboration, and multimodal perception [1] - The medical large model simulates clinical thinking for complex reasoning, achieving precise differential diagnosis and evidence-based decision-making, supported by a vast amount of quality medical data and proprietary knowledge base [1] Performance Metrics - In the MedBench 4.0 evaluation system, the company achieved scores of 94.6, 65.7, and 59.6 in medical intelligent agents, large language models, and multimodal large models respectively, securing the top position in all three technical paradigms [2] - The company's medical large model has been successfully implemented in numerous top-tier hospitals, demonstrating its clinical practical value and adaptability to industry standards and clinical needs [2]

香港交易及結算所有限公司及香港聯合交易所有限公司對本公告的內容概不負責，對其準確性或完整性亦不發表 任何聲明，並明確表示概不就因本公告全部或任何部分內容而產生或因倚賴該等內容而引致的任何損失承擔任何 責任。 UNISOUND AI TECHNOLOGY CO., LTD. 雲知聲智能科技股份有限公司 （於中華人民共和國註冊成立的股份有限公司） （股份代號：9678） 自願性公告 最新技術進展 本公告乃由雲知聲智能科技股份有限公司（「本公司」）自願作出，旨在知會本公司股東 及潛在投資者有關本公司的最新技術發展情況。 近日，本公司發佈醫療領域專家大模型「山海‧知醫大模型5.0」版本（「醫療大模型」）， 構建「醫學文本大模型+醫學多模態大模型」雙核心產品體系，全面覆蓋文本處理、智能 體協同、多模態感知等核心能力，整合醫學知識問答、臨床任務規劃、影像解析等多元 功能，形成當前業界能力維度最豐富的醫療AI技術支撐體系之一。醫療大模型能夠深度 模擬臨床思維進行複雜推理，實現精準鑒別診斷與循證決策。本公司依託海量優質醫療 數據與專屬知識庫訓練，在醫學知識問答、信息抽取等核心任務中達到業界頂尖水平； 通過持續課程學習、知識圖 ...

Market Performance - Last week, Hong Kong stocks showed a rebound, with the Hang Seng Index, the Hang Seng China Enterprises Index, and the Hang Seng Tech Index rising by 0.8%, 0.7%, and 1.1% respectively[1] - Large insurance and domestic bank stocks performed steadily in the latter half of the week, supporting the market's recovery[1] - The pharmaceutical sector saw a rebound after the U.S. Senate passed the revised 2026 National Defense Authorization Act, benefiting companies like WuXi Biologics and WuXi AppTec[1] Sector Highlights - The automotive sector rebounded significantly, with XPeng Motors rising by 7.6% after receiving an L3 autonomous driving road test license in Guangzhou[4] - The healthcare sector's Hang Seng Medical Care Index fell by 1.8% overall but rose by 1.7% on Friday, indicating a potential recovery[5] - The renewable energy and utilities sectors experienced a general decline, although the photovoltaic sector saw slight gains due to expected policy support[6] Economic Indicators - The U.S. Michigan Consumer Sentiment Index for December was reported at 52.9, below Bloomberg's forecast of 53.5 but above the previous value of 51.0[3] Investment Opportunities - The upcoming IPO of Insilico Medicine, a prominent AI-driven drug discovery company, is noteworthy due to its rapid revenue growth and strong backing from reputable investors[5] - The recent policy on e-cigarette regulation is expected to create new opportunities for compliance-driven growth in the domestic market[1]

Core Insights - The integration of general AI into the medical field faces challenges in ensuring that algorithms understand clinical needs and can be effectively embedded into treatment processes, marking a critical transition from "usable" to "practical" AI in healthcare [6][8] Group 1: AI Development and Implementation - Yidu Technology is focusing on a systematic reconstruction aimed at clinical practicality, utilizing its self-developed medical domain model "YiduCore" to create a dual-platform solution combining big data and large models [6][8] - The AI platform aims to transform the raw capabilities of large models into "intelligent agents" that comply with medical standards, understand clinical workflows, and possess specialized knowledge [6][7] Group 2: Trust and Integration in Clinical Settings - To achieve reliable applications of medical AI, Yidu Technology emphasizes bridging the trust gap between patients, doctors, and AI through three core capabilities: a high-quality knowledge center, a comprehensive library of over 40 intelligent algorithms, and seamless integration into natural workflows [7][8] - The "Doctor Clinical Copilot" is designed as a lightweight plugin that integrates into doctors' workstations, facilitating real-time AI assistance in critical tasks such as medical record writing and treatment planning [7][8] Group 3: Practical Applications and Impact - Yidu Technology has developed intelligent applications that address specific clinical tasks, significantly altering the modes and efficiencies of diagnosis and treatment in specialized fields [8][9] - In cardiology, the AI platform integrates over 20 cardiovascular guidelines to provide real-time analysis and decision support, enhancing the efficiency of knowledge retrieval and diagnostic capabilities for urgent scenarios [8] - In oncology, the AI system has improved the accuracy of tumor staging assessments to 90% and reduced computational demands, while also creating a digital twin of a chest tumor expert to offer personalized consultations [8][9] Group 4: Future Outlook - Yidu Technology plans to continue leveraging its dual-platform solution and intelligent agent matrix to deepen its impact across more specialized fields, aiming to enhance the precision and efficiency of healthcare services [9]

Market Overview - On December 18, A-shares showed mixed performance with the Shanghai Composite Index rising by 0.16% to 3876.37 points, while the Shenzhen Component Index fell by 1.29% to 13053.97 points, and the ChiNext Index decreased by 2.17% to 3107.06 points [1] - The total trading volume in the Shanghai and Shenzhen markets reached 1.66 trillion yuan, with nearly 2900 stocks rising across the market [1] Sector Performance - The banking sector experienced a rebound, with Shanghai Bank rising over 3% [1] - Retail concepts showed strength, with Central Plaza and Shanghai Jiubai hitting the daily limit [1] - The commercial aerospace sector was active, with Shengyang Technology achieving two consecutive limits and Shunhao Co. hitting the daily limit [1] - The pharmaceutical retail sector continued its strong performance, with Luyan Pharmaceutical achieving two consecutive limits and Zhongyao Holdings hitting four limits in seven days [1] - The IP economy concept was also active, with Guobo Co. and Sanxiang Impression hitting the daily limit [1] Market Statistics - A total of 61 stocks hit the daily limit, with 17 stocks achieving consecutive limits, and 19 stocks failed to hit the limit, resulting in a limit rate of 76% (excluding ST and delisted stocks) [1] Notable Stocks - Major stocks hitting the daily limit included: - Baida Group (retail) [8] - Pinao (custom home) [8] - Li Qun Co. (retail chain) [8] - Central Plaza (retail) [8] - Shengyang Technology (commercial aerospace) [9] - Luyan Pharmaceutical (healthcare) [9] Emerging Trends - The AI application in healthcare is gaining traction, with Ant Group's AI health application "Antifufu" surpassing 15 million monthly active users as of December 15 [10] - The global healthcare AI market is expected to grow at a compound annual growth rate of 43% from 2024 to 2032, potentially reaching a market size of $491 billion [10]