Jiangxi Rimag Group Co., Ltd. 江西一脈陽光集團股份有限公司 （於中華人民共和國註冊成立的股份有限公司） 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所產生或因依 賴該等內容而引致的任何損失承擔任何責任。 本公告由江西一脈陽光集團股份有限公司（「本公司」，連同其附屬公司統稱「本集 團」）董事（「董事」）會（「董事會」）自願作出。 董事會欣然宣佈，2025 年 4 月 2 日，本公司的附屬公司北京一脈陽光醫學 信息技術有限公司（「北京一脈信息」）「C T胸部病變標注數據」（掛牌編號： 1571967301-YLIIIEJ5101）（「數據集」）正式通過上海數據交易所合規審核並成功 上架。這是本公司首批在上海數據交易所上架的數據集，也是繼本公司構建覆蓋 全國醫學影像數據生態鏈後，在醫療數據資產化領域的里程碑及突破，且標誌著 本公司以高質量的影像數據為紐帶，率先打通「數據生產及治理 － 算法和技術 － 場景賦能」的閉環，使醫學影像數據要素市場化進程邁入新階段，本公司也正在 逐步用 ...

Summary of Medical Data Circulation and Trading Conference Call Industry Overview - The conference call discusses the medical data industry in China, focusing on the circulation and commercialization of medical data assets, particularly in major hospitals in Beijing and other cities like Shenzhen and Shanghai [1][2]. Key Points and Arguments 1. **Expansion of Medical Data Trials**: In 2024, the Beijing Health Commission and Economic and Information Bureau will expand medical data trials to 22 major hospitals, promoting the assetization of medical data [1][2]. 2. **Challenges in Data Sharing**: Hospitals face challenges such as low levels of information technology and insufficient data demand. Solutions include improving IT infrastructure, clarifying data needs, and providing policy and financial support [1][3]. 3. **Policy as a Driving Force**: National policies are crucial for the circulation of medical data. The National Data Bureau actively promotes data sharing plans and encourages hospitals to open their data elements [1][2]. 4. **Demand for Specialized Data**: Hospitals prefer to trade representative specialized disease data, with demand typically driven by commercial value [1][4]. 5. **AI's Impact on Data Demand**: The development of AI in healthcare has significantly increased the demand for medical data, shifting focus from basic medical records to high-value data such as expert notes on complex cases [1][6]. 6. **Lack of Standard Pricing**: There is no unified pricing standard for medical data, which is usually based on asset valuation and costs associated with technical teams and data annotation [1][6]. 7. **Data Ownership Issues**: The issue of data ownership is a major barrier to commercial applications. Anonymization is key, as anonymized data can belong to hospitals, facilitating data circulation [1][12][16]. 8. **Successful Case Studies**: Successful data trading cases, such as the orthopedic data assetization by Jishuitan Hospital, demonstrate the potential for hospitals to monetize their data [2][5]. 9. **Regulatory Environment**: The regulatory environment is evolving, with Beijing providing clear guidelines for medical data transactions, encouraging innovation and pilot projects [4][21]. 10. **Collaboration Among Hospitals**: Hospitals are exploring collaborative models for data standardization and revenue sharing, which could serve as a benchmark for future projects [13][20]. Additional Important Insights - **Diverse Data Needs**: Different types of data, such as imaging and clinical data, are in demand, with top hospitals being preferred sources due to their quality and quantity of data [7][10]. - **Non-Exclusive Data Sales**: Data can be sold to multiple buyers unless there is an exclusivity agreement, which can increase the price [8]. - **Impact of Population Size**: China's large population provides a vast amount of high-quality medical data, which is advantageous for developing medical AI models [14]. - **Third-Party Collaborations**: Third-party companies can collaborate with hospitals to develop specialized AI models, provided they follow legal and compliance processes [22][23]. - **Future of Data Standardization**: Efforts are underway to standardize and connect medical data across regions, although challenges remain [11][30]. This summary encapsulates the key discussions and insights from the conference call regarding the medical data industry, highlighting the opportunities and challenges in data circulation and commercialization.