Group 1 - The core viewpoint of the articles revolves around the advancements in AI technology within the healthcare sector, particularly through the initiatives of Shulan Medical, which has launched its AI health assistant, Dr. Shu, and is actively pursuing a strategy focused on computational medicine [2][10][19] - Shulan Medical has established strategic partnerships with various data intelligence companies to enhance its smart healthcare initiatives and implement its AI future medical strategy [2][10] - The founder and president of Shulan Medical, Zheng Jie, emphasizes the importance of computational medicine as a systematic and mechanism-driven paradigm for precision healthcare, which integrates multiple disciplines including statistical learning and AI technology [2][4][19] Group 2 - The concept of computational medicine is gaining traction globally, with initiatives like the EU's virtual human twin database and the NIH's Bridge2AI project in the US, which focus on multi-modal data construction to support precision medicine [3][4] - Shulan Medical's roadmap for computational medicine includes steps from data standardization to life modeling, aiming to create a patient-centered digital twin for personalized medical decision-making [3][4][5] - The development of electronic medical records (EMR), electronic health records (EHR), and personal health records (PHR) is crucial for building a comprehensive data foundation for computational medicine [5][6] Group 3 - The Open Medical and Healthcare Alliance (OMAHA), founded by Zheng Jie, aims to promote machine-readable standards for healthcare data, which is essential for achieving data interoperability and supporting the development of computational medicine [6][7] - OMAHA has introduced the HiTA technology stack, which enhances the interoperability of medical data and provides a high-quality standardized data foundation for personal health databases [7][10] - The transition from static data to dynamic data is highlighted through the development of personal digital twins (PDT), which aim to closely replicate human life through comprehensive information modeling [7][10] Group 4 - The rapid development of medical AI has led to its integration into various healthcare applications, with a focus on improving hospital operational efficiency, patient services, and research capabilities [10][11] - Shulan Medical's AI health assistant, Dr. Shu, is designed to enhance patient interaction and streamline the healthcare process by providing pre-diagnosis, diagnosis assistance, and post-treatment follow-up [12][13] - The digital twin concept is being explored to provide remote medical services, allowing for more personalized and efficient healthcare delivery [12][14] Group 5 - Shulan Medical's "All in Technology" strategy aims to reconstruct future healthcare models through computational medicine, integrating AI and wearable technologies to offer comprehensive health services [17][19] - The upcoming AI Future Health Medical Center is set to combine various healthcare technologies to create a seamless health service experience for users [18][19] - The focus on building a feedback loop between AI healthcare capabilities and real-world data is essential for enhancing the accuracy and accessibility of AI-driven medical services [18][19]

作为一名"极客"，郑杰对生命科学有着天然的好奇。2013年底，在"互联网+医疗"的风口下，郑杰再次 突破创新边界，创立树兰医疗。这一次，他不再仅仅作为技术提供者，而是构建了一个融合前沿技术与 真实医疗场景的生态平台。 2025年，生成式AI的爆发式发展正深刻重塑医疗健康产业格局。 你是否有设想过这样一个场景：当AI不再是冰冷的工具，一位老人迟暮时，AI有着他所有的健康数 据，从出生时的基因编码到不同生命阶段的历史病例，那或许就意味着，未来AI可以让每个生命阶段 的健康变化都可以被预见。 在树兰医疗集团（简称"树兰医疗"）的愿景中，已经构建这样一个全生命周期的健康医疗服务目标。作 为社会办医的先行者，树兰医疗正逐渐将自身打造为集健康医疗服务、医学科研、医学教育为一体的科 技型医疗集团。 或许是从计算机专业毕业，树兰医疗集团创始人、总裁郑杰让"科技赋能医疗"成为树兰医疗创新发展轨 迹的生动注脚。近日，新京报贝壳财经记者约访郑杰，解码创新型医疗集团的成功之道，与他共同展望 树兰医疗的下一个十年。 "极客"跨界 医疗集团深植科技基因 "计算机普及要从娃娃抓起。"这句掷地有声的号召，在1984年推动了中国计算机教育的浪 ...