上午，招聘会刚开始，各个展位前就围满前来咨询和投递简历的毕业生。江苏省中医院的招聘人员 表示，开始后两个小时就收到三四百份简历。正在筹建中的江苏省脑科医院首次参会公开招聘。据院方 介绍，该院为省级精神专科医院，已于2024年9月开工建设，预计2028年底投入使用，本次计划招聘精 神卫生专业人才39人，包括30个专业型硕士岗位和9个博士岗位，全部面向精神卫生学临床医师。江苏 省脑科医院综合组高雨蓓表示："我们收到的简历来源广泛，除南京医科大学、东南大学等本地高校 外，还有温州医科大学、安徽医科大学等，最远有牡丹江医科大学的毕业生前来应聘。"南京医科大学 第二附属医院的展位前也人头攒动。南医大二附院组织人事处副处长曲晨透露，该院此次提供了超过 100个岗位，以临床科室为主，涵盖内科、外科、妇产科、儿科等，招聘重点为博士及硕士等高层次人 才。 据了解，大会参会单位200余家，覆盖省、市、县（区）、乡（镇）不同层级。参与本次招聘会的 单位不仅涵盖省卫生健康委员会直属的22家事业单位，还包括南京鼓楼医院、东南大学附属中大医院、 南京市儿童医院、明基医院等医院，招聘专业涉及医、药、护、技和管理等多个领域，招聘学历涵盖专 ...

Core Points - The strategic cooperation between Nanjing First Hospital and Qinhuai District Health Commission marks a significant step in implementing the "Healthy China" strategy and enhancing the hierarchical medical service system in Nanjing [1][2] - The partnership aims to integrate high-quality medical resources and improve healthcare services at the grassroots level, ensuring that residents can access tertiary hospital-level services locally [2][3] Group 1: Strategic Cooperation - The signing ceremony signifies the beginning of a new phase in the construction of a tightly-knit urban medical group, emphasizing the hospital's commitment to public health and social responsibility [1] - Nanjing First Hospital will leverage its expertise in cardiovascular, respiratory, and rehabilitation fields to empower grassroots medical institutions [1][2] Group 2: Implementation and Development - The cooperation will involve the establishment of five specialized centers, including hypertension management and cardiovascular care, to create an integrated service loop for prevention, treatment, management, and rehabilitation [2][3] - The initiative aims to transform the medical alliance from a "loose" to a "tight" model, focusing on resource sharing and collaborative development among healthcare providers [3] Group 3: Future Goals - The partnership seeks to enhance the capabilities of grassroots healthcare through talent cultivation and the establishment of a robust medical workforce [3] - Nanjing First Hospital will continue to promote management, technology, talent, and cultural sharing, aiming to create an efficient and collaborative medical service system [3]

Core Viewpoint - The event held in Changsha on November 6 highlighted the contributions of outstanding medical professionals in China, emphasizing their dedication and selflessness in serving the community [1] Group 1: Event Overview - The event was organized by the Central Spiritual Civilization Construction Office and the National Health Commission, focusing on the second batch of "Chinese Good Doctors and Good Nurses" for 2025 [1] - A total of 30 exemplary healthcare workers from the health system were honored during the event [1] Group 2: Stories of Medical Professionals - The event featured various storytelling formats, including videos and interviews, showcasing the commitment of healthcare workers who have made significant sacrifices [1] - Some honorees have worked in remote areas, earning the title of "Good Mamba" (Good Doctor), while others returned to their hometowns to serve their communities [1] - The event included tributes to historical figures, with veterans recalling the bravery of medical personnel during the Anti-Japanese War, urging current healthcare workers to uphold these traditions [1] Group 3: Impact and Future Commitment - The "Chinese Good Doctors and Good Nurses" initiative has conducted 24 exchange activities across 20 provinces, promoting high-quality development in the health sector [1] - Young healthcare professionals expressed their determination to follow the examples set by these role models to contribute to the advancement of health services [1]

Core Insights - The US services sector activity returned to expansion in October, with the ISM services PMI recorded at 52.4%, up from 50% in September, marking the eighth consecutive month above the threshold [1] - The business activity index rose significantly to 54.3%, a 4.4 percentage point increase from September's 49.9%, indicating a return to expansion [1] - The new orders index surged to 56.2%, a rise of 5.8 percentage points, reflecting improved demand in the services sector [1] Industry Performance - Eleven industries experienced growth in October, including accommodation and food services, retail, wholesale, real estate, healthcare, and transportation and warehousing [2] - Six industries faced contraction, including arts and entertainment, management services, finance and insurance, public administration, and construction [2] Employment and Inventory Trends - The employment index remained in contraction at 48.2%, indicating weak hiring intentions despite a slight improvement from September [1] - The inventory index recorded at 49.5%, still in contraction, as businesses generally reduced inventory levels to manage demand and cost uncertainties [2] Price and Supply Chain Dynamics - The prices index rose to 70%, the highest level since October 2022, indicating persistent inflationary pressures in the services sector, driven by tariffs affecting material and service costs [1] - The supplier deliveries index stood at 50.8%, indicating a continued slowdown in delivery speeds, which is typically associated with improved demand or supply chain constraints [1] Order Backlog and Economic Signals - The backlog of orders index dropped significantly to 40.8%, the second-lowest level since 2009, suggesting that businesses can manage current orders without significant delivery delays [2] - Feedback from industries indicated mixed economic signals, with some sectors experiencing seasonal demand improvements while others faced challenges from import restrictions and rising prices [2]

Group 1 - The Hang Seng Index fell by 0.28%, down 73 points, closing at 25,878 points, while the Hang Seng Tech Index decreased by 0.80%. The early trading volume in Hong Kong stocks was HKD 138.2 billion [1] - AI concept stocks experienced a decline, with concerns over high valuations. Institutions suggest that the long-term outlook for Hong Kong tech stocks remains attractive [1] - Hui Liang Technology (01860) dropped over 6%, and Kingsoft (03888) fell by 2.81% [1] Group 2 - Longpan Technology (603906) saw an increase of over 9% as lithium battery midstream prices continue to rise, with institutions expecting further price momentum [2] - Yimai Sunshine (02522) rose by 3.27% following several directors' share purchases, and the "AI + healthcare" sector is expected to benefit from new policies [3] - China Duty Free Group (601888) (01880) increased by over 4%, marking its first interim dividend, with recent policies likely to boost the duty-free industry [3] Group 3 - Yihua Tong (02402) surged by 7.7%, with significant cash flow improvement in the first three quarters, and fuel cell vehicle production is expected to accelerate [4] - Tianli International Holdings (01773) rose by 4.9%, with its AI learning companion already implemented in over 100 schools nationwide [5] - Mixue Group (02097) increased by 2.89%, planning to collaborate with Anjun Express for cold chain operations in Brazil [6] Group 4 - Huishang Bank (03698) rose by 4%, reporting a net profit of CNY 14.149 billion in the first three quarters, with institutions indicating potential for future growth [7] - Sanhua Intelligent Control (002050) (02050) fell by 1.94%, as Goldman Sachs pointed out overly optimistic robot expectations, while the market is focused on Tesla's trillion-dollar compensation plan [7] - Home Control (01747) dropped by 13%, facing scrutiny from the Hong Kong Securities and Futures Commission due to high stock ownership concentration [7] - Long Fiber Optic (601869) (06869) declined by 2.81%, with Q3 net profit down nearly 11%, and UBS stated that the impact of hollow-core fiber on profitability is limited in the short term [7]

Market Overview - The Hang Seng Index fell by 0.28%, down 73 points, closing at 25,878 points, while the Hang Seng Tech Index decreased by 0.80%. The early trading volume in Hong Kong stocks was HKD 138.2 billion [1]. AI Sector - AI concept stocks experienced a decline, with concerns over high valuations intensifying. Institutions suggest that the long-term outlook for Hong Kong tech stocks remains attractive. HuiLiang Technology (01860) dropped over 6%, and Kingsoft (03888) fell by 2.81% [1]. Lithium Battery and Healthcare - Longpan Technology (02465) saw a midday increase of over 9% due to ongoing price hikes in the lithium battery midstream, with institutions predicting further price momentum. Yimai Sunshine (02522) rose by 3.27% following several directors' share purchases, indicating a positive outlook for the "AI + healthcare" sector amid new policies [1]. Duty-Free Industry - China Duty Free Group (01880) rose over 4% against the market trend, marking its first interim dividend. Recent policy developments are expected to boost growth in the duty-free industry [1]. Fuel Cell Vehicles - Yihua Tong (02402) increased by 7.7%, with significant cash flow improvement in the first three quarters, and the potential for accelerated release of fuel cell vehicles [1]. Other Companies - Tianli International Holdings (01773) rose by 4.9% as its AI companion has been implemented in over 100 schools nationwide [2]. - Mixue Group (02097) increased by 2.89% due to a planned cold chain cooperation with Anjun Express in Brazil [3]. - Huishang Bank (03698) rose by 4%, reporting a net profit of CNY 14.149 billion for the first three quarters, with expectations for future inclusion in the stock connect [3]. - Sanhua Intelligent Control (02050) fell by 1.94% as Goldman Sachs indicated overly optimistic robot expectations, with market attention on Tesla's trillion-dollar compensation plan [4]. - HOME CONTROL (01747) dropped by 13% after being named by the Hong Kong Securities and Futures Commission for high shareholding concentration [5]. - Changfei Optical Fiber and Cable (06869) fell by 2.81%, with Q3 net profit declining nearly 11%. UBS stated that the impact of hollow-core fiber on profitability is limited in the short term [6].

Core Insights - The National Health Commission and five other departments have jointly issued implementation opinions to promote and regulate the application of "Artificial Intelligence + Healthcare" [1] - By 2027, the goal is to establish high-quality health industry data sets and trusted data spaces, along with the widespread application of intelligent decision-making and patient service systems in healthcare institutions [1] Group 1: Clinical Diagnosis - The implementation opinions emphasize the promotion of intelligent diagnostic services in medical imaging, supporting the collective development of AI-assisted diagnosis and report generation in provincial hospitals [2] - There is a focus on enhancing diagnostic efficiency and report quality by expanding AI-assisted diagnosis from single diseases to multiple diseases affecting single organs [2] - High-level hospitals are encouraged to gather and develop high-quality medical imaging data for AI model research and upgrades [2] Group 2: Health Industry Development - The implementation opinions support collaboration between medical equipment manufacturers and healthcare institutions to advance intelligent medical equipment development [2] - Key areas for intelligent upgrades include medical imaging, diagnostic testing, treatment, monitoring, and life support equipment [2] - There is encouragement for the application of domestically produced intelligent medical equipment in healthcare institutions, particularly for innovative tasks in AI medical devices [2]

Core Insights - The National Health Commission released implementation opinions to promote and regulate the application of "Artificial Intelligence + Healthcare," outlining eight key application areas and development goals for 2027 and 2030 [1][2]. Group 1: Key Application Areas - The eight key areas identified include AI + grassroots applications, AI + clinical diagnosis, AI + patient services, AI + traditional Chinese medicine, AI + public health, AI + research and education, AI + industry governance, and AI + health industry [2][3]. - The focus on grassroots applications aims to enhance intelligent services in areas such as medical imaging, ECG diagnosis, and public health management [3]. Group 2: Development Goals - By 2027, the goal is to establish high-quality health data sets and intelligent applications in clinical settings, with a focus on major diseases and enhancing diagnostic capabilities [2][4]. - By 2030, the aim is for intelligent applications in grassroots diagnosis to achieve full coverage, with advanced AI applications in secondary and tertiary hospitals [2]. Group 3: Company Opportunities - A-share companies like Shanhai Mountain, Yunnan Baiyao, and Aojiahua have already made early investments in AI + healthcare, positioning themselves to benefit from the policy's support [1][4]. - Companies such as Keda Xunfei and Yunkang Life are developing AI solutions for imaging and comprehensive healthcare services, enhancing patient experience and operational efficiency [4][5]. Group 4: Focus on Medical Robots - The implementation opinions emphasize the promotion of intelligent medical devices, including rehabilitation and acupuncture robots, indicating a growing market for AI-driven medical equipment [5]. - Companies like Aojiahua are developing smart massage robots based on traditional Chinese medicine principles, showcasing innovation in the sector [5]. Group 5: Patient Services and Research - The implementation opinions highlight the need for AI to enhance patient services, including intelligent appointment scheduling and pre-consultation services in hospitals [5][6]. - Companies like Yunnan Baiyao are advancing drug research through AI systems that predict the effects of new molecules, indicating a trend towards integrating AI in pharmaceutical research [6].

Core Viewpoint - The article discusses the implementation opinions on promoting and regulating the application of "Artificial Intelligence + Healthcare" in China, outlining a strategic framework for the development of AI in the healthcare sector by 2027 and 2030 [1][4]. Group 1: Overall Requirements - The guiding ideology emphasizes government guidance, multi-party participation, innovation-driven approaches, and safety control, aiming to meet the growing health service demands of the public [7]. - By 2027, the goal is to establish high-quality datasets and trusted data spaces in the healthcare sector, with widespread applications of AI in clinical decision-making and patient services [7][8]. - By 2030, the aim is for comprehensive coverage of intelligent assistance in grassroots diagnosis and the establishment of a standard system for AI applications in healthcare [8]. Group 2: Deepening Key Applications - AI applications will focus on eight areas, including grassroots healthcare, clinical diagnosis, patient services, traditional Chinese medicine, public health, scientific research, industry governance, and health industry development [9][10][11][12]. - Specific initiatives include enhancing intelligent applications in community healthcare, promoting intelligent diagnostic services in medical imaging, and improving management of chronic diseases [9][10]. Group 3: Strengthening Application Foundations - Emphasis on infrastructure development, including the construction of a national health information platform connecting all healthcare institutions [14]. - The article highlights the need for rich medical data supply and optimized AI algorithms, as well as the establishment of comprehensive co-creation platforms for AI applications [15][16]. Group 4: Regulating Safety and Supervision - Proposals include optimizing industry management and review systems, innovating regulatory methods, and enhancing data security and personal privacy protection [17]. Group 5: Strengthening Organizational Support - The article calls for improved institutional frameworks, pilot demonstrations, and collaborative promotion of AI in healthcare to ensure mutual benefits and shared outcomes [17].

11月4日，国家卫健委等五部门联合发布《关于促进和规范"人工智能+医疗卫生"应用发展的实施意见》(以下简称《意见》)。《意见》明确2027年、2030年 两阶段发展目标，从基层应用、临床诊疗、患者服务到中医药、公共卫生等八大方向部署24项重点任务。不仅通过人工智能赋能解决基层医疗资源短缺、临 床诊疗效率不足等民生痛点，更将通过中试基地建设、智能装备研发、数据要素激活，为行业打开增量市场，在支撑卫生健康事业高质量发展的同时，进一 步发挥医疗领域海量数据（603138）与巨大市场应用规模优势，培育壮大大健康产业，推动健康产业从传统服务型向智能技术驱动型转型。 《意见》明确，到2027年，建立一批卫生健康行业高质量数据集和可信数据空间，形成一批临床专病专科垂直大模型和智能体应用，基层诊疗智能辅助、临 床专科专病诊疗智能辅助决策和患者就诊智能服务在医疗卫生机构广泛应用，基本建成一批医疗卫生领域国家人工智能应用中试基地，打造更多高价值应用 场景，带动健康产业高质量发展。 到2030年，基层诊疗智能辅助应用基本实现全覆盖，推动实现二级以上医院普遍开展医学影像智能辅助诊断、临床诊疗智能辅助决策等人工智能技术应 用，"人工智 ...