MDDI 演讲稿 · 2025-03-19
陈杰豪高级政务部长在 AI 健康世界峰会 2025 上的开幕致辞
Opening Address by SMS Tan Kiat How at AI Health World Summit 2025
要点
- • 新加坡医疗行业 AI 早期采用——放射科最早用 AI 检测影像异常；近期 SingHealth「Note Buddy」实时多语种问诊转写。
- • 「个性化干预」案例：SGH 的 AI2D（个性化抗生素处方，降低耐药风险）；AI Singapore 的 CURATE.AI（个性化化疗剂量）。
- • 「上游预防」案例：aiTriage（仅靠 ECG + 手机 App 预测 3 / 30 天心脏事件风险，7 分钟分诊）；CARES²（术后并发症预测）；NUS × CMU × FriendsLearn 在新加坡建「数字疫苗」精准预防卓越中心。
- • 新启动「SingHealth Duke-NUS AI in Medicine Institute」（AIMI）——四大优先：前沿 AI 研究（基础模型 + 智能体 AI）、AI 素养、研究到落地的桥梁、伦理治理。
- • $1.2 亿新元投入「AI for Science」计划——支持 AI 与科研的融合（含生物医学）。Synapxe「HEALIX」平台整合公立医院数据基础设施。
- • 今天见证 SingHealth × CHAI（Coalition for Health AI，美国非营利，成员含 Google、Johns Hopkins、梅奥诊所、微软、斯坦福医学院）签署 MOU——共建 AI 医疗指南、出版物与政策建议。
完整译文（中文）
MDDI 英文原文译文 · 翻译日期：2026-05-03
本文已从早期版本的网站迁移过来——格式可能有不一致之处。
SingHealth 集团首席执行官 Ng Wai Hoe 教授，
Duke-NUS 医学院研究高级副院长 Patrick Tan 副教授，
A*STAR 生物医学研究理事会助理首席执行官 Lisa Ooi 博士，
「Coalition for Health in AI」首席执行官 Brian Anderson 博士，
各位嘉宾、代表、
来自世界各地的朋友们：
早安。我很高兴出席第三届「AI Health World Summit」（AI 健康世界峰会）。
我向 SingHealth Duke-NUS 学术医学中心与 A*STAR 致敬——他们把这一跨边界、跨学科、跨产业的社群召集到一起。
今天在场的我们都共享同一个目标——改造我们社区的医疗——并都相信 AI 在实现这一目标中扮演重要角色。
新加坡一直是「用技术克服多种约束」的坚定信仰者——土地、劳动力、小型市场。
在这一点上——AI 是一项有重大潜能的技术。
我们的医疗行业很早就拥抱了 AI。
a. 比如——我们的放射科医生是「用 AI 检测医学影像异常」最早的采用者之一。
生成式 AI 进一步打开了「临床效率」的新可能。
a. 一个例子是去年 8 月推出的 SingHealth「Note Buddy」工具。
b. 这一工具实时转写并总结问诊——并支持多种语言。
c. 它减少了医生的行政工作量——让他们与病人有更多有意义的互动。
重要的是——AI 也让我们能在「规模化、低成本」的同时，对医疗干预采取「更个性化」的方法。
a. 一个例子是新加坡总医院（SGH）的「AI2D」（Augmented Intelligence in Infectious Diseases）模型——个性化为患者开抗生素，降低抗生素耐药的风险。
b. 另一个例子是 AI Singapore 的「CURATE.AI」——为个体患者优化化疗剂量。
c. 不再只把医疗干预建立在「群体级临床试验」之上——这些早期努力有可能通过让决策反映个人独特的「基因、生活方式、病史」相关的生物标志物反应——改善干预结果。
AI 也增强了我们的预测能力——让医生能把更多干预「向上游推进」——朝预防性照护方向走。
a. 比如——SGH、Duke-NUS、DxD Hub 共同开发的心脏风险工具「aiTriage」——能预测病人在未来 3 天或 30 天内出现重大心脏事件的风险。
i. 仅用一台 ECG 设备与手机 App——医护人员就能识别高危患者并在 7 分钟内做出分诊——显著提高心脏骤停的存活率。
b. 这种早期检测能力在围手术期医学中也很有价值——「CARES 2」就是这样的手术风险模型。
i. 由 SGH 与新加坡国立大学（NUS）共同开发——能预测术后并发症的可能性、并提示是否需要再入院或入 ICU。这类预测让早期干预成为可能。
AI 给了我们「再向上游推进」的工具——比如——如何及早塑造行为、在症状出现之前大幅降低疾病风险。
a. 一个例子是——NUS 的医学院与计算学院、卡内基梅隆大学（CMU）的 Heinz 信息系统与公共政策学院——以及作为技术发明者与转化伙伴的 FriendsLearn Inc 之间的合作。
b. 他们将在新加坡建立一个「精准预防 AI 卓越中心」——通过我们所谓的「数字疫苗」。
c. 这些「数字疫苗」使用神经认知训练、内隐学习、沉浸式游戏——以安全有效的方式——为儿童培育健康行为——同时为神经发育与肠道菌群健康打底。
d. 这能在童年「习惯形成」的关键阶段——在神经-生理层面引发并强化与「行为与选择」相关的变化。我们期待跟踪这种方法如何为后代改善「终身的健康与认知福祉」。
我们才刚刚触及 AI 给医疗带来的巨大可能性的表层。
a. 前沿项目正在改造我们「研究病理与设计医疗干预」的方式。
b. 比如——Google DeepMind 的新系统「AlphaProteo」——能为与癌症、糖尿病相关的蛋白生成新的「分子结合体」（molecule binders）——帮助调控关键的细胞过程。
c. 我们正在更接近「靶向曾被认为『不可成药』的蛋白」——以及「曾被认为不可治愈的疾病」。
d. 借助这些进展——也许有生之年我们能治愈更多种癌症！
这些进展的影响是深远的。
同样令人惊叹的是——它们出现于不同领域的交汇——计算机科学、分子生物学、临床医学等等。
这种「专长的汇流」提醒我们——最大的突破不是仅靠技术——而是把多元的头脑带到一起。
这种跨学科对话——必须从把生态的不同部分聚到一起开始。
a. 这就是为什么——我们的国家健康科技机构 Synapxe 去年推出「HEALIX」分析平台——以整合公立医院的数据基础设施。借助一个统一、安全的 AI 开发平台——HEALIX 让基于「匿名化国家级数据」的分析项目成为可能。
我们也在弥合「研究」与「临床落地」之间的鸿沟。在最近的国会预算辩论中——副总理王瑞杰谈到了「双语」人才的重要性——把 AI 研究与领域专长结合的研究者——就像今天在场的许多位。
对「应用 AI 研究」的聚焦至关重要。政府已为「AI for Science」计划承诺投入 1.2 亿新元——这一倡议支持 AI 与科研的整合——包括生物医学与健康科学领域。
为持续把研究流向实践——我们将继续为「跨学科学习与应用」搭建平台。
今天——我很高兴启动「SingHealth Duke-NUS AI in Medicine Institute」（AIMI，AI 在医学领域研究院）。
a. 这个研究院将把 SingHealth 与 Duke-NUS 医学院的专长汇集起来——四大优先：
i. 第一——领跑前沿 AI 技术研究——包括基础模型与智能体 AI。
ii. 第二——倡导 AI 素养——在医疗专业人士与公众中培育「知情采用」的文化。
iii. 第三——弥合研究与真实世界应用之间的鸿沟——推动创新 AI 项目的全球商业化。
iv. 第四——主导制定稳健的伦理指南——强调负责任 AI、患者安全、数据隐私。
这一研究院的优先事项——也凸显了我们前方的几项挑战。
上一次（2023 年）举办这一峰会时——生成式 AI 刚刚席卷世界。从那以后——全球对 AI 的视角已经成熟——对它的实际收益与风险有了更清晰的认识。
「信任」必须是我们的北极星。
信任一直是医疗的根基——我们的社区、我们的病人——把生命托付给我们。
但有了 AI——我们走在「医疗突破」与「风险」之间的细微界线上。从「算法透明度」到「不具代表性的训练数据」——种种挑战可能损害 AI 方案的安全性，并侵蚀患者对医疗机构与专业人士的信任。
因此——即便我们在「实验与创新」新技术——我们也不能丢掉「稳健的治理」与「以患者结果为中心」。
我们必须把发展过程中的关键利益相关方聚在一起——临床医生、研究者、决策者，重要的——还有患者及其家属。
正是这种集体努力——构建出信任——协作与共同承诺会带来持久的信心。这就是为什么像今天这样的峰会很关键。
本着这种精神——我也很高兴见证 SingHealth 与「Coalition for Health AI」（CHAI）签署 MOU。
a. CHAI 是一家位于美国的非营利组织——致力于在医疗中为「安全、有效、公平的 AI」建立指南与最佳实践。
b. CHAI 把学术医疗体系、机构与专家实务者聚到一起——成员包括 Google、约翰霍普金斯大学、梅奥诊所、微软、斯坦福医学院。
今天签署的 MOU——是双方共同承诺——提升医疗中「负责任 AI 使用」的认知。
a. 这将包括共同制定 AI 指南、出版物与政策建议——确保医疗 AI 使用持续保持伦理、透明，并聚焦于改造病人照护。
前方有许多激动人心的机会与可能——作为社群、作为社会、作为人类。但让我们始终记住——AI 在医疗中成功的真正衡量——不是技术进步——而是它「改善生命」的能力。
祝大家峰会顺利。
英文原文
MDDI 官网原始记录 · 抓取日期：2026-05-02
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Professor Ng Wai Hoe, Group CEO of SingHealth
Associate Professor Patrick Tan, Senior Vice-Dean of Research at Duke-NUS Medical School
Dr Lisa Ooi, Assistant Chief Executive of the Biomedical Research Council at A*STAR
Dr Brian Anderson, CEO of the Coalition for Health in AI
Distinguished speakers, delegates
Friends from around the world
A very good morning and it is my pleasure to join you today at the third AI Health World Summit.
I commend the SingHealth Duke-NUS Academic Medical Centre and A*STAR for convening this community from across borders, disciplines, and industries.
All of us here have the shared goal to transform healthcare in our communities and are joined in the belief that AI plays an important role to achieve this aim.
Singapore has always been a firm believer in using technology to overcome our many constraints – land, labour and small market size.
In this regard, AI is a technology with significant potential.
Our healthcare sector had embraced AI early on.
a. For example, our radiologists were amongst the earliest adopters in using AI to detect anomalies in medical scans.
Generative AI has further opened up new possibilities for clinical efficiency.
a. An example is SingHealth’s Note Buddy tool that was launched last August.
b. The tool transcribes and summarises consultations in real-time and in different languages.
c. It reduces the doctors’ administrative workload, freeing them to have more meaningful interactions with their patients.
Importantly, AI has also given us the capability to adopt a more personalised approach to medical intervention, at scale and at lower cost.
a. An example is the Singapore General Hospital’s AI2D (Augmented Intelligence in Infectious Diseases) model. The model personalises antibiotic prescriptions for patients, reducing the risk of antibiotic resistance.
b. Another example is AI Singapore’s CURATE.AI that optimises chemotherapy doses for individual patients.
c. Instead of basing medical interventions just on population-based clinical trials, these early efforts have the potential to improve intervention outcomes by enabling decisions to be informed by an individual’s unique responses to biomarkers related to genetics, lifestyle, and medical history.
AI also improves our predictive capabilities, allowing doctors to shift more interventions upstream towards preventive care.
a. For example, aiTriage, a cardiac risk tool developed by the Singapore General Hospital, Duke-NUS Medical School, and DxD Hub, can predict a patient’s risk of a major cardiac event in the next 3 or 30 days.
i. Using just an ECG device and mobile app, healthcare workers can identify at-risk patients and make triaging decisions in under 7 minutes, thereby significantly improving the chances of someone surviving a cardiac arrest.
b. These early detection capabilities are also valuable in peri-operative medicine. CARES 2 is one such surgical risk model.
i. Developed by the Singapore General Hospital and National University of Singapore, it can predict the likelihood of post-operation complications, and inform the need for re-admission or ICU admission. These predictions facilitate early interventions.
AI gives us the tools to go further upstream, for example looking at how we can shape behaviours early and reduce disease risks well before symptoms emerge.
a. An example is a partnership between the National University of Singapore's Schools of Medicine and Computing, and Carnegie Mellon University's Heinz College of Information Systems and Public Policy, along with FriendsLearn Inc – a technology inventor and translation partner.
b. They will establish a Centre of Excellence in Singapore for the use of AI in precision prevention, via what we call ‘digital vaccines’.
c. These digital vaccines use neurocognitive training, implicit learning, and immersive gaming to encourage healthier behaviours in children – safely and effectively priming neurodevelopment and gut biome health.
d. This induces and reinforces changes at the neuro-physiological level underlying behaviours and choices, during the critical habit-formation stage of childhood. We look forward to tracking how this method can improve lifelong health and cognitive wellbeing for generations to come.
We are scratching at the surface of the immense possibilities that AI brings to healthcare.
a. Cutting-edge projects are transforming the way we study pathology and design medical interventions.
b. Take for example Google Deepmind’s new AlphaProteo system. It can generate new molecule binders for proteins associated with cancer and diabetes, helping regulate critical cellular processes.
c. We are coming closer to targeting proteins once thought ‘undruggable’, and conditions thought incurable.
d. With these advances, we can possibly cure many more forms of cancer in our lifetime!
The implications of these advances are profound.
But equally remarkable is how they've emerged from the intersection of different fields – computer science, molecular biology, clinical medicine and more.
This convergence of expertise reminds us that our greatest breakthroughs come not from technology alone, but from bringing diverse minds together.
Such interdisciplinary conversations must begin by bringing together different parts of the ecosystem.
a. This is why our national healthtech agency, Synapxe, launched its HEALIX analytics platform last year to consolidate data infrastructure across our public hospitals. With a unified secure platform for AI development, HEALIX makes analytics projects with anonymised national data possible.
We are also bridging the gap between research and clinical implementation. At the recent Budget Debate in Parliament, DPM Heng spoke of the importance of ‘bilingual’ talent – researchers who combine AI research with domain expertise like many of you in the audience here today.
This focus on applied AI research is crucial. The Government has committed $120 million to the AI for Science programme. This initiative supports the integration of AI and scientific research, including in the biomedical and health sciences fields.
To sustain this flow of research to practice, we will continue investing in platforms for interdisciplinary learning and application.
Today, I am pleased to launch the SingHealth Duke-NUS AI in Medicine Institute, or AIMI.
a. This Institute will bring together expertise from SingHealth and Duke-NUS Medical School, with four priorities.
i. First, to spearhead research in frontier AI technologies, including foundation models and agentic AI.
ii. Second, to champion AI literacy, fostering a culture of informed adoption amongst healthcare professionals and the public alike.
iii. Third, to bridge the gap between research and real-world application, driving the global commercialisation of innovative AI projects.
iv. Fourth, to lead the development of robust ethical guidelines, which emphasise responsible AI, patient safety, and data privacy.
The priorities of this institute highlight some of the challenges that lie ahead of us.
When we last held this Summit in 2023, GenAI had just taken the world by storm. Since then, global perspectives towards AI have matured, with a clearer view of its actual benefits and risks.
Trust must be our North Star.
Trust has always underpinned healthcare; our communities, our patients entrust us with their lives.
But with AI, we tread a fine line between medical breakthroughs and risks. Challenges from algorithmic transparency to unrepresentative training data may undermine the safety of AI solutions, and erode patients’ trust in the healthcare institutions and professionals.
That is why we must not lose sight of robust governance and the focus on patient outcomes even as we experiment and innovate with new technologies.
We must bring together key stakeholders in the development process - clinicians, researchers, policymakers, and importantly patients and their families.
It is this collective effort that builds trust, where collaboration and shared commitment lead to lasting confidence. This is why efforts like today’s Summit are critical.
It is in this spirit that I am also heartened to witness the signing of an MOU between SingHealth and the Coalition for Health AI, or CHAI.
a. CHAI is a US-based non-profit organisation, dedicated to establishing guidelines and best practices for safe, effective, and equitable AI across healthcare.
b. CHAI brings together academic health systems, organisations, and expert practitioners, with members including Google, Johns Hopkins University, Mayo Clinic, Microsoft, and Stanford Medicine.
The MOU being signed today is a pledge of commitment by both organisations to raise awareness of responsible AI use in healthcare.
a. This will involve the co-creation of AI guidelines, publications, and policy recommendations, ensuring that the use of AI in healthcare remains ethical, transparent, and focused on transforming patient care.
There are many exciting opportunities and possibilities lie ahead of us – as a community, as society, as humanity. But let us always remember the true measure of AI’s success in healthcare is not the technical advancements but its ability to improve lives.
I wish everyone a fruitful Summit.