不同于大模型在C端市场的应用多聚焦于泛娱乐化以引流，在B端市场，大模型的应用天然要求精准、 高效，健康产业尤其如此。 据《华夏时报》记者了解，京医千询大模型于2023年上线，今年2月对外全面开源，6月升级至2.0版 本。据京东方面介绍，京医千询2.0实现了对文本、影像、检验报告等多模态医学数据的深度融合解 析，是行业首个能看懂医学报告、听懂病情描述的医疗大模型，也是行业首个可信推理模型。京东健康 探索研究院相关负责人还表示，京医千询的核心目标是通过技术渐进式逼近人类医生的临床认知边界。 本报（chinatimes.net.cn）记者卢晓 北京报道 "在我们长期投入AI能力建设的过程中，实践证明，医疗AI的价值，绝不是单纯技术参数的比拼，而是 要融入临床场景、解决实际问题。"9月25日，京东健康CEO金恩林在京东全球科技探索者大会（下 称"JDD大会"）期间对《华夏时报》等媒体记者这样说道。 当天，京东健康宣布京医千询医疗大模型2.0版本升级，并推出全新的"AI医院1.0"。在这背后，随着全 球AI热潮掀起，AI正在重构各个产业的供应链，大模型与产业间的深度融合也正加速落地，而高质量 数据则成为这场融合的关键。 ...

Group 1 - JD Group announced the JDD 2025 Global Technology Explorer Conference will be held on September 25 in Beijing, focusing on the theme "Enjoy AI" [1] - The main forum will showcase a series of products and demonstrate the deep application of AI in JD's various scenarios, with the new model brand JoyAI being widely applied across hundreds of scenarios [1] - Afternoon specialized forums will decode the industrial practice paths of AI, including discussions on AI Infra upgrades and the release of JoyAgent 3.0, as well as opportunities in supply chain finance under the "National Subsidy" policy [1][2] Group 2 - The conference will feature the Super AI interactive experience area with ten technology exploration spaces, including practical AI agents and emotional companion AI toys [2] - Since 2017, JD has invested over 150 billion yuan in R&D and operates 20,000 intelligent agents, aiming to reshape the efficiency boundaries in retail, logistics, and healthcare through deep integration of AI and industry [2] - JDD 2025 serves as a platform for showcasing AI innovation and driving industrial intelligent transformation, demonstrating how technological innovation can transition from laboratories to households [2]

Core Viewpoint - The article discusses the emergence of leading players in the healthcare sector as the hype subsides and the market stabilizes, particularly focusing on the growth of innovative drugs and AI healthcare in China [1][2][3]. Group 1: Market Trends - In the first half of the year, Chinese A/H share innovative drug companies saw stock prices rise by 78%, while some AI healthcare stocks experienced gains exceeding 100% [3]. - The healthcare sector is experiencing a resurgence, reminiscent of the internet healthcare boom over a decade ago, but with a more serious and sustainable approach [4][5]. Group 2: Company Performance - JD Health reported a revenue of 35.29 billion yuan for the first half of the year, marking a 24.5% year-on-year increase, with active user numbers surpassing 200 million [6][7]. - The company achieved a gross profit of 8.89 billion yuan, reflecting a 32.7% increase, and operating profit surged by 105.5% to 2.13 billion yuan [7]. Group 3: Industry Dynamics - The healthcare industry is expected to undergo a cooling period, with predictions of a more stable growth trajectory following a previous surge in 2019-2020 [9][10]. - In 2025, healthcare is positioned as a key focus area in policy frameworks, with initiatives aimed at promoting the integration of medical services and innovative healthcare models [11]. Group 4: Competitive Advantages - JD Health's competitive edge lies in its robust supply chain and comprehensive service offerings, including a one-stop solution for medication, diagnostics, and treatment [15][24]. - The company has established itself as a leader in the innovative drug market, launching over 30 new drugs in the first half of 2025, and has expanded its online pharmacy network significantly [22][23]. Group 5: AI Integration - JD Health is at the forefront of AI healthcare, having launched its AI triage and prescription review solutions as early as 2019, and has since developed a comprehensive AI product matrix [29][30]. - The introduction of AI-driven digital twins of doctors has significantly improved consultation efficiency, serving over 50 million users by mid-2025 [31].

Core Viewpoint - JD Health reported a revenue of 35.29 billion RMB for the first half of 2025, marking a 24.5% increase year-on-year, with a non-IFRS profit of 3.57 billion RMB, up 35% from the previous year, indicating a steady improvement in profitability [2][3]. Financial Performance - Revenue for the first half of 2025 reached 35.29 billion RMB, compared to 28.34 billion RMB in 2024, reflecting a growth of 24.5% [3]. - Gross profit was 8.89 billion RMB, with a gross margin of 25.2%, indicating a strong historical performance [2][3]. - Operating profit increased significantly by 105.5% to 2.13 billion RMB, while pre-tax profit rose by 17.4% to 2.86 billion RMB [3]. Market Position and Challenges - Despite strong financial performance, JD Health's stock price remains low due to perceived reliance on pharmaceutical sales rather than high-value medical services, with over 83% of revenue coming from drug sales [5]. - The internet healthcare sector is experiencing intense competition, with major players like Alibaba Health and Ping An Good Doctor, as well as traditional pharmacies transitioning to digital platforms [5]. - Regulatory risks in the pharmaceutical industry, including drug price controls and online sales regulations, pose challenges to JD Health's business model [6]. Strategic Insights - The healthcare industry is expected to grow due to factors like an aging population and increased health awareness, suggesting a potential for long-term growth in the health sector [4]. - JD Health's integration of AI technology into its services could enhance profitability and operational efficiency, with initiatives like "AI Jingyi" already serving over 50 million users [10][11]. - The company aims to increase the proportion of revenue from healthcare services, which could improve its overall profitability structure [11].

Core Insights - The article discusses the integration of AI in healthcare, emphasizing that while AI can enhance medical services, it cannot replace human doctors. The focus is on the development of AI models by major companies to address the shortage of quality medical resources and improve patient care [2][5][23]. Group 1: AI Models and Companies - Tencent launched the "Tencent Medical Model" in September 2023, focusing on intelligent diagnosis and electronic medical records [3]. - JD Health released the "Jingyi Qianxun" model in July 2023, enhancing its AI capabilities in the healthcare ecosystem [3]. - Ant Group introduced the "Ant AQ" model, exploring the synergy between healthcare and insurance [3]. - iFLYTEK's "Spark Medical Model" was released in October 2023, with its "Smart Medical Assistant" passing the national medical practitioner qualification test [3]. Group 2: Comparison of AI Models - Ant AQ provides a comprehensive consultation experience, simulating a face-to-face interaction with a doctor, while Quark offers a lightweight, search-based experience [6][18]. - Ant AQ's design allows for multi-round questioning to gather detailed patient information, creating a more personalized interaction [13][15]. - Quark focuses on providing structured answers and is seen as a reliable information source rather than a diagnostic tool [18][21]. Group 3: Strategic Approaches - Ant AQ aims for a deep service model, integrating AI throughout the patient journey from pre-diagnosis to post-care, effectively acting as a personal health assistant [26][28]. - Quark positions itself as an information gateway, emphasizing authoritative health knowledge without engaging in direct diagnosis [29][30]. - Both models serve as assistants to doctors rather than replacements, highlighting the importance of human oversight in medical decisions [23][41]. Group 4: Market Growth and Challenges - The Chinese medical AI market grew from 2.7 billion yuan in 2019 to 10.7 billion yuan in 2023, with projections reaching 97.6 billion yuan by 2028 [37]. - The article notes the need for rigorous clinical validation of AI models before they can be widely adopted in healthcare settings [38][41]. - Ethical considerations regarding data privacy and the integration of AI into the patient-doctor relationship are critical for the successful deployment of these technologies [41][42].

Core Viewpoint - The integration of AI technology into the healthcare industry is essential for addressing challenges such as global aging, chronic disease burdens, and uneven distribution of medical resources, positioning AI as a systemic solution for sustainable healthcare development [1][3][4]. Group 1: AI Empowerment in Healthcare - AI has transitioned from pilot scenarios to ecosystem restructuring, enhancing efficiency and accessibility in healthcare services [8][11]. - The forum highlighted the need for a new medical data infrastructure to achieve breakthroughs in efficiency, value, and equity [9][11]. - AI applications in healthcare are rapidly evolving, with significant advancements in areas such as pediatric AI pre-consultation, digital imaging in dentistry, and remote dermatology consultations [11][15]. Group 2: Sustainable Innovation in Healthcare - The "2025 Sustainable Innovation Case Recommendation List" was released, showcasing 37 cases from 36 well-known domestic and foreign companies, focusing on urgent industry needs and aligning with the Healthy China 2030 strategy [6][18]. - The list categorizes cases into "International Innovation Localization," "Local Innovation Globalization," and "ESG Innovation Practices," aiming to promote experience sharing and resource integration within the industry [6][18][35]. Group 3: Globalization and Localization Strategies - Multinational companies are deepening localization strategies, evolving from local production to local R&D innovation, while leveraging their technological and resource advantages to foster local innovation [35][41]. - Chinese pharmaceutical companies are increasingly exploring international markets, integrating into the global innovation ecosystem, and ensuring that local innovations benefit a global audience [35][41]. Group 4: ESG and AI in Healthcare - ESG has become a core issue for sustainable development, with a growing focus on integrating AI technology ethics into ESG evaluation dimensions [48]. - Companies are encouraged to disclose AI model training data sources and bias correction mechanisms, ensuring compliance and ethical standards in AI applications [48]. Group 5: Future Directions and Challenges - The healthcare industry faces challenges in high-quality data sample supply and the translation of clinical research into practical applications [11][13]. - The need for a robust AI infrastructure that supports effective business models and enhances traditional services is emphasized, with a focus on data-driven decision-making [50][51].

Group 1 - The forum focused on the integration of AI in the healthcare industry, addressing challenges such as aging populations and uneven distribution of medical resources, emphasizing AI as a systemic solution for sustainable healthcare development [1][3] - The Shanghai government highlighted the importance of deep integration between AI and healthcare as a strategic choice to enhance public health and foster new productive forces [3] - The forum featured nearly 20 speakers from various sectors discussing topics like AI-driven innovation in healthcare and the globalization of local enterprises [5] Group 2 - The "2025 Sustainable Innovation Case Recommendation List" was launched, showcasing 37 cases from 36 well-known companies, categorized into "International Innovation Localization," "Local Innovation Globalization," and "ESG Innovation Practices" [5][15] - The cases highlighted urgent industry needs and aligned with China's health strategy for 2030, aiming to provide actionable innovation pathways [5][15] - The forum emphasized the need for collaboration among stakeholders to create a vibrant ecosystem for AI in healthcare [3][5] Group 3 - AI in healthcare is transitioning from pilot projects to ecosystem restructuring, with applications like pediatric AI pre-consultation and remote dermatology gaining traction [7][9] - Challenges remain, including insufficient high-quality data samples and the gap between clinical research and application [9][11] - China is evolving from a passive technology importer to an active innovator in the global pharmaceutical landscape, with significant increases in licensing deals [11][22] Group 4 - The "2025 Sustainable Innovation Case Recommendation List" includes notable companies such as Bayer, Pfizer, and Medtronic in the "International Innovation Localization" category [17][19] - Local companies like Aier Eye Hospital and Junshi Biosciences are recognized for their global innovation efforts [18][22] - ESG practices are increasingly important, with companies like Philips and JD Health showcasing their commitment to sustainable development [24][25] Group 5 - The forum discussions highlighted the importance of AI as a foundational infrastructure for healthcare innovation, with ESG serving as a critical framework for sustainable practices [32][34] - The integration of AI in healthcare is seen as essential for addressing common challenges such as resource distribution and operational efficiency [30][36] - The need for a collaborative approach among various stakeholders, including regulatory bodies and healthcare providers, was emphasized to ensure the successful implementation of AI technologies [30][32]

Core Insights - The 2025 World Artificial Intelligence Conference (WAIC) was held in Shanghai, where JD Health showcased its latest AI achievements, particularly the advancements of the "Jingyi Qianxun" medical model and its future directions [1][4] - JD Health's medical AI solutions were included in the "2025 Sustainable Innovation Case Recommendations" list, highlighting its industry-leading position in medical model technology innovation and AI application [1][5] Group 1: JD Health's AI Model Developments - JD Health's self-developed medical model "Jingyi Qianxun" has been continuously upgraded to version 2.0 since its full open-source release in February, focusing on expanding AI applications from general services to more complex specialized fields [2] - The "Jingyi Qianxun 2.0" model features a "three engines + four models" architecture, which includes evidence-based data, clinical case engines, and patient-doctor interaction simulation engines, aimed at enhancing the capabilities of its four models [2][3] Group 2: Technological Breakthroughs - Significant breakthroughs have been achieved in "human-like dialogue," "trustworthy reasoning," and "medical multimodality," enhancing user experience and ensuring reliable medical reasoning through extensive clinical evaluations [3] - The model's ability to analyze multimodal medical data, including text, images, and test results, supports precise diagnosis and treatment [3] Group 3: Industry Recognition and Impact - The "2025 Sustainable Innovation Case Recommendations" were established to recognize AI's deep application in healthcare, addressing critical issues like accessibility and affordability of medical services [5][6] - JD Health has launched several AI medical products, including "AI Jingyi," "JD Zhuoyi," and "Kangkang," covering various healthcare scenarios from online consultations to health management [6] Group 4: Product Expansion and User Engagement - JD Health's internet hospital has launched over 500 expert doctor AI agents, making it the largest platform in terms of the number of AI agents and service scale in the industry [9] - The AI doctor "Daiwei" has significantly improved its capabilities, serving over one million users within a month and achieving a service satisfaction rate exceeding 97% [9] Group 5: Future Directions - JD Health aims to deepen its focus on medical AI, enhancing the value of large models in more scenarios to provide high-quality, efficient, and professional healthcare services to a broader audience [10]

Group 1 - The 2025 World Artificial Intelligence Conference (WAIC) held in Shanghai featured the "AI + Healthcare Industry Sustainable Innovation Forum," where the "2025 Healthcare Sustainable Innovation Case Recommendation List" was released, highlighting the importance of technology in promoting healthcare accessibility and social value creation [1][3] - JD Health's medical AI model solution was recognized in the recommendation list, showcasing its leading advantages in technological innovation and practical application [1][3] - The recommendation list was initiated by multiple organizations, including Yicai Media and the Shanghai Modern Service Industry Association, aiming to discover and celebrate outstanding cases that promote sustainable innovation in the healthcare sector [3] Group 2 - The AI Sustainable Innovation Case Nomination Committee emphasized that accelerating the deep application of AI is crucial for addressing the public's pain points regarding healthcare accessibility and affordability [3] - JD Health has launched the first fully open-source vertical model in the domestic medical industry, "Jingyi Qianxun," along with a series of AI medical products such as "AI Jingyi," "JD Zhuoyi," and "Kangkang," covering various healthcare scenarios [3][5] - "AI Jingyi" has served over 50 million users in just six months and has introduced over 500 intelligent expert doctor agents, establishing a comprehensive AI health service matrix [3][5] Group 3 - At the WAIC 2025 exhibition area, JD Health showcased its AI medical products, generating significant interest and interaction among attendees [5] - JD Health's Chief Scientist, Wang Guoxin, stated that since the full open-source launch in February, the company has focused on developing "Jingyi Qianxun 2.0" to advance AI in healthcare from general services to more complex specialized fields [5]

Core Insights - AI is driving the transformation and upgrading of the healthcare industry, becoming a strategic high ground for technology empowering people's livelihoods [1] - The evolution of AI in healthcare is transitioning from "assistance tools" to "intelligent participation" due to advancements in large model technology and multi-modal capabilities [2][10] - The AI healthcare ecosystem consists of three core layers: data and computing power, algorithm models and platform capabilities, and various application scenarios [1][13] Group 1: AI Healthcare Overview - AI healthcare is defined as a systematic solution based on AI technology for deep learning, pattern recognition, and intelligent decision-making to assist in diagnosis, optimize resource allocation, and improve efficiency [1] - The industry is experiencing a paradigm shift with the emergence of large models that support unified understanding and task adaptation of multi-modal medical data [2] - The AI healthcare ecosystem includes traditional healthcare, AI healthcare service, and AI healthcare technology product ecosystems, which are interdependent and collaboratively developed [13][14] Group 2: Application Scenarios - AI is widely used in medical imaging diagnosis, pathology recognition, and clinical decision support, enhancing service capabilities and diagnostic efficiency [3] - In the medical payment sector, AI aids in claims review, intelligent cost control, and personalized pricing, leading to refined management [3] - AI is also empowering genomics and molecular biology, facilitating personalized treatment pathways and pushing precision medicine into clinical practice [3] Group 3: Market Overview - The global AI healthcare market is transitioning from a "technology breakthrough" phase to a "deployment" phase, with significant growth expected, from $29.01 billion in 2024 to $50.42 billion by 2032, at a CAGR of 44.0% [18][19] - In contrast, China's AI healthcare market is in a critical transition from "technology validation" to "value validation," with market size growing from 2.7 billion yuan in 2019 to 10.7 billion yuan in 2023, projected to reach 97.6 billion yuan by 2028 [19][22] Group 4: Development History - The evolution of AI in healthcare can be divided into three stages: medical informationization, internet healthcare, and intelligent healthcare, with the current transition from "internet healthcare" to "intelligent healthcare" [7][10] - AI is deeply integrated into the entire process of pre-diagnosis, diagnosis, and post-diagnosis, utilizing technologies like AI large models, medical robots, AR/VR, and 5G [7][10] Group 5: Business Opportunities - The emergence of large models is reshaping AI healthcare technology, enabling complex medical scenarios and enhancing the efficiency of healthcare professionals [2][25] - The medical data market is expected to activate with the establishment of a compliant data sharing mechanism, transforming medical data from "sleeping assets" to "efficient elements" [2][25] - AI is expected to create a closed-loop system of "data-model-scenario-payment," becoming a key driver for high-quality development in the healthcare system [3][11] Group 6: AI Medical Payment - AI in medical payment is becoming a key engine for improving the efficiency of medical insurance and commercial insurance systems, covering claims review, cost control, and fraud detection [47][48] - The application of AI in the medical payment sector is evolving from "process automation" to "risk control intelligence" and "actuarial-driven" approaches [49] Group 7: Gene Sequencing - The cost of gene sequencing is rapidly decreasing, driven by the introduction of AI and parallel computing, with costs dropping to below $100 for whole genome sequencing [52][53] - The gene sequencing industry is maturing, with applications in research and clinical fields, including non-invasive prenatal testing, tumor diagnosis, and precision treatment [52][56]