MDDI 演講稿 · 2025-05-27
Rahayu Mahzam 政務次長在 AI 健康研討會 2025 上的閉幕致辭
要點
- • 新加坡醫療 AI 三原則：「解決真實問題」+「負責任地規模化」+「廣泛協作」。
- • 新加坡總醫院 + GovTech 合作的 Proph Abby——AI 助理把抗生素處方對指南的合規率從 80% 提至 95%、複雜病例時間節省最高 90%。
- • BiliSG（SGH × SingHealth × Synapxe）讓父母在家用智慧手機給新生兒做黃疸篩查；MerMed-FM（SingHealth × A*STAR 合作的醫療基礎模型）讓小型機構也能基於 AI 起步。
- • 信任與治理：HSA 早在 2019 年釋出 AI 醫療裝置指南；2021 年 MOH+IHiS（現為 Synapxe）+ HSA 聯合釋出《醫療 AI 指南》；TRUST 健康資料交換平臺支援匿名分析。
- • 當日見證兩份合作備忘錄：Enigma Health × Roche 把 AI 與製藥能力結合服務臨床試驗；Enigma Health × ST Engineering 把醫療創新帶給最懂患者需求的人。
完整譯文（繁體中文）
MDDI 英文原文譯文 · 翻譯日期: 2026-05-03
瑞士駐新加坡大使 Frank Grütter 閣下，
各位嘉賓、產業領袖、醫療專業人士、女士與先生：
開場
我很高興今天為「AI 在健康領域研討會——以生成式 AI 規模化與可持續化醫療」做閉幕。
和其他國家一樣——新加坡的醫療系統面對人口結構演變與生活方式變化帶來的挑戰。我們的人口在老齡化，慢性疾病的患病率在上升。這些挑戰給醫療專業人士與醫院基礎設施帶來壓力——也呼喚新的醫療交付方式。
因此——藉助技術「以有效且負責任的方式交付優質護理」對我們至關重要。AI 在「改造我們如何照護病人、支援醫療工作者、構建更具韌性的健康系統」上有巨大潛力。
我很高興看到——今天的會議讓大家有機會有意義地審視新加坡的醫療創新方法。讓我把我們方法之下的幾個關鍵考量講清楚。
解決真實問題
第一——我們採取務實的方法，把 AI 與技術應用到醫生與病人面對的真實問題上。我們走「證據為本、價效比為先」的路——看哪裡能產生最大影響。
新加坡總醫院（SGH）每年完成超過 10 萬臺手術，每一臺都需要預防性抗生素。但選對抗生素並不簡單——醫生必須考慮手術型別、病人過敏史與疾病史。SGH 與 GovTech 的「開放政府產品」（Open Government Products）團隊合作開發了「Proph Abby」——幫助醫生在複雜病例中——按既定指南——開出正確的抗生素。這把 AI 直接嵌入到臨床流程中——幫助醫生更高效地交付護理。
在測試中——這款 AI 助理對既定指南的合規率達到 95%——較之前醫生 80% 的合規率有顯著改進。它在複雜病例上還能為醫生節省最多 90% 的時間。這個例子說明——AI 同時改善了病人結果與護理效率。
我們也在把醫療帶得離家庭與家人更近。黃疸影響超過半數的新生兒——這要求多次往返門診——讓脆弱的嬰兒暴露於潛在感染——也讓新家庭備受壓力。「BiliSG」由 SGH、SingHealth Polyclinics、Synapxe 共同開發——讓父母用智慧手機 App 在家就能為新生兒篩查黃疸。BiliSG 的試點 App 達到了高度精準的靈敏度——並減少了不必要的門診就診。它正在兒科醫院與綜合診所做進一步測試。
這些機會令人印象深刻——但需要被廣泛獲得。為醫療用例開發定製基礎模型，需要大量資料集與資源。這可能形成一種「鴻溝」——只有大型、資金充裕的機構能從 AI 進展中獲益，小醫院與診所被甩在後面。因此——我們也必須把 AI 能力的獲取「民主化」。
想想 SingHealth 與 A*STAR 共同開發中的「MerMed-FM」基礎模型。這個模型旨在以「比傳統方法更少的訓練資料」讓 AI 開發更高效。如果成功——MerMED-FM 能讓較小的醫療機構在不必從零開始的情況下構建 AI 應用。
負責任地規模化
但即便我們在解決痛點——也必須負責任地去做。
畢竟——生成式 AI 帶來強大的新能力的同時——也帶來關於隱私、安全與信任的新風險——我們必須回應。
「Enigma」是 Enigma Health 推出的醫療 AI 平臺，自動化醫院的行政工作。在 KK 婦女兒童醫院與 PRISM¹（SingHealth Duke-NUS 精準醫學研究所）開展的試點中——Enigma 把每份基因報告的撰寫時間從 30 分鐘縮短到幾秒——一小時可處理 1,400 份，原本需要數週。重要的是——資料隱私得以保留。
「ELVF-FM」是 SingHealth 與 A*STAR 的研究合作——旨在幫助醫生解讀醫學影像、驗證臨床結果。如果成功——這款工具會高亮其檢測到的異常並解釋自身推理——它有望克服許多今天 AI 系統的「黑箱」屬性——讓 AI 應用更安全。
在單一應用之外——我們還需要構建支撐創新的安全基礎設施。比如健康研究——能幫助我們理解疾病、開發新治療、規劃健康專案、改進公共衛生政策——但必須以維護公眾信任、保障個人隱私的方式進行。新加坡國家級的健康相關資料交換平臺「TRUST」²（Trusted Research and Real World Data Utilisation and Sharing Tech）——通過安全基礎設施與一套穩健框架，支援匿名化的大規模分析。研究在「受控訪問 + 經過稽核的輸出」下進行——但不涉及個人識別符。
Enigma、ELVF-FM 與 TRUST——為我們展示瞭如何在「保持被信任」的同時駕馭 AI 的力量。
在醫療 AI 的採用中——「良好治理」與「技術進展」同等關鍵。沒有清晰規則——公司不敢投資、醫生不敢採納新技術。
這就是為什麼——新加坡衛生科學局（HSA）早在 2019 年就引入 AI 醫療裝置指南、提供清晰監管路徑。2021 年——衛生部、當時的「整合健康資訊系統」（IHiS，現為 Synapxe）與 HSA——在此基礎上聯合釋出《醫療 AI 指南》。
廣泛協作
但即便是最精密的技術與最穩健的治理框架——也無法獨立成功。醫療轉型需要集體努力、共享專長。
沒有一家機構能獨自應對醫療 AI 的複雜性。我們必須跨行業、跨利益相關方協作——在公共與私營部門之間。
今天——我很高興見證兩份諒解備忘錄的簽署：一份是 Enigma Health 與羅氏（Roche），另一份是 Enigma Health 與新科工程（ST Engineering）。
這兩份 MOU 體現了我們對醫療創新的協作式做法。
通過這次合作——Enigma Health 與羅氏將把 AI 能力與製藥專長結合起來——加強臨床試驗與市場準入。這一合作將幫助創新治療更高效地抵達病人。
Enigma Health 與新科工程的合作——會讓醫療創新更易被「最懂病人需求」的人獲得。
總體上——這些「解決真實問題、負責任規模化、廣泛協作」的努力——讓新加坡能借力 AI 增強醫療中的人類專長，從而為新加坡與新加坡人交付更好結果。
感謝各位為本次研討會做出的貢獻——感謝你們成為新加坡為後代構建更好醫療這一旅程的一部分。
我真心相信——攜手同行——我們能為所有人構建更健康的未來。祝大家日安。
1 SingHealth Duke-NUS 精準醫學研究所
2 Trusted Research and Real World Data Utilisation and Sharing Tech（受信任的研究與真實世界資料利用與共享平臺）
英文原文
MDDI 官網原始記錄 · 抓取日期: 2026-05-02
His Excellency Mr Frank Grütter, Ambassador of Switzerland to Singapore
Distinguished guests, industry leaders, healthcare professionals, ladies and gentlemen.
Opening
It is my pleasure to close today’s AI in Health symposium on "Scaling and Sustaining Healthcare with GenAI".
Like other countries, Singapore’s healthcare system faces challenges arising from the evolving demography and changing lifestyles. Our population is aging and the prevalence of chronic illnesses is on the rise. These challenges create pressures on our healthcare professionals and hospital infrastructure. These pressures demand new ways of delivering care.
It is therefore important that we harness technology to deliver quality care in a way that is effective and responsible. AI offers tremendous potential to transform the way we care for patients, support our healthcare workers and create more resilient health systems.
I am heartened to note that the session today has allowed for a meaningful examination of Singapore’s approach to healthcare innovation. Let me articulate some key considerations underlying our approach.
Solve real problems
First, we take a practical approach and apply AI and technology to solve real-world problems for clinicians and patients. We take an evidence-based, cost-effective approach and look at areas where we can make the most impact.
Singapore General Hospital (SGH) performs over 100,000 surgeries annually, each requiring prophylactic antibiotics. But choosing the right antibiotic is complex and takes time. Doctors must consider the type of surgery, patient allergies and medical conditions. Working with the Open Government Products team at GovTech, SGH developed Proph Abby to help doctors prescribe the right antibiotics for complex cases, against established guidelines. This directly embeds AI into clinical flows to help clinicians deliver care more efficiently.
In testing, the AI assistant achieved 95% compliance with established guidelines: a significant improvement over the previous 80% compliance rate by doctors. It also saves doctors up to 90% of time on complex cases. This exemplifies how AI improves both patient outcomes and care efficiency.
We are also bringing healthcare closer to homes and families. Jaundice affects more than half of newborn babies. This requires multiple trips to the clinic, exposing vulnerable infants to potential infections and creating stress for new families. BiliSG, developed by SGH, SingHealth Polyclinics and Synapxe, helps parents screen their newborns for jaundice using a smartphone application, from the comfort of their homes. BiliSG’s pilot app achieved highly precise sensitivity and reduced unnecessary clinic visits. It is now undergoing further tests in paediatric hospitals and polyclinics.
These opportunities, while impressive, need to be made widely available. Developing customised foundational models for medical use cases requires massive datasets and significant resources. This can create a divide where only large, well-funded institutions can benefit from AI advances, while smaller hospitals and clinics are left behind. Hence, we must also democratise access to AI capabilities.
Consider MerMed-FM, a foundational model that SingHealth and A*STAR are co-developing. The model aims to make AI development more efficient by requiring lesser training data than traditional methods. If successful, MerMED-FM could enable smaller healthcare facilities to build AI applications without starting from scratch.
Responsible scaling
But even as we solve pain points, we need to do it responsibly.
After all, while Generative AI brings powerful new capabilities, it also raises new risks about privacy, safety and trust which we must address.
Enigma, a healthcare AI platform by Enigma Health, automates hospital administrative work. At KK Women's and Children's Hospital and PRISM 1 , a pilot with Enigma cut genetic reporting time from 30 minutes per report to just seconds, or 1,400 reports in an hour, instead of weeks. Importantly, data privacy is preserved.
ELVF-FM, a research collaboration between SingHealth and A*STAR, seeks to help doctors interpret medical images, and verify clinical results. If it succeeds, the tool will highlight the abnormalities that it detects and explains its reasoning. It could overcome the ‘black box’ nature of many AI systems today, enabling safer AI applications.
Beyond individual applications, we need to build secure infrastructure that enables innovations. For instance, health research can help us understand more about health conditions, develop new medical treatments, plan health programmes and improve public health policy, but it must be done in a manner that upholds public trust and preserves individuals’ privacy. TRUST 2 , Singapore’s national health-related data exchange platform, supports this by putting in place secure infrastructure and a robust framework to enable anonymised at-scale analytics. Research is done with controlled access and vetted outputs, but without involving personal identifiers.
Enigma, ELVF-FM and TRUST offer a glimpse of how we can harness the power of AI while remaining trusted.
Good governance is just as crucial as technological advances in advancing the adoption of AI in healthcare. Without clear rules, companies hesitate to invest, and doctors hesitate to adopt new technologies.
This is why Singapore's Health Sciences Authority (HSA) provided clear regulatory pathways when it introduced AI medical device guidelines in 2019. In 2021, the Ministry of Health, the then-Integrated Health information Systems (IHiS), now Synapxe, and the HSA built on this foundation by publishing the Artificial Intelligence in Healthcare Guidelines.
Collaborate widely
Yet even the most sophisticated technology and robust governance frameworks cannot succeed in isolation. Healthcare transformation requires collective effort and shared expertise.
No single institution can tackle the complexity of healthcare AI alone. We need to collaborate across sectors and stakeholders, between the public and private sectors.
Today, I am glad to have witnessed the two MOU signings between Enigma Health and Roche as well as Enigma Health and ST Engineering.
The two MOUs exemplify our collaborative approach to healthcare innovation.
Through their partnership, Enigma Health and Roche will combine AI capabilities with pharmaceutical expertise to strengthen clinical trials and market access. This collaboration will help bring innovative treatments to patients more efficiently.
The partnership between Enigma Health and ST Engineering will make healthcare innovation more accessible to those who understand patient needs best.
Collectively, these efforts to solve real problems, scale responsibly, and collaborate widely enables Singapore to leverage on AI to augment human expertise in healthcare, thereby delivering better outcomes for Singapore and Singaporeans.
Thank you for your contributions to this symposium, and for being part of Singapore’s journey to build better healthcare for generations to come.
I truly believe that together we can build a healthier future for all. Have a good day ahead.
1 SingHealth Duke-NUS Institute of Precision Medicine
2 Trusted Research and Real World Data Utilisation and Sharing Tech