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Closing Address by MOS Rahayu Mahzam at AI in Health Symposium 2025

27 May 2025

His Excellency Mr Frank Grütter, Ambassador of Switzerland to Singapore

Distinguished guests, industry leaders, healthcare professionals, ladies and gentlemen.

Opening

  1. It is my pleasure to close today’s AI in Health symposium on "Scaling and Sustaining Healthcare with GenAI".

  2. 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.

  3. 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.

  4. 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

  1. 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.

  2. 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.

  3. 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.

  4. 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.

  5. 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.

  6. 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

  1. But even as we solve pain points, we need to do it responsibly.

  2. After all, while Generative AI brings powerful new capabilities, it also raises new risks about privacy, safety and trust which we must address.

  3. Enigma, a healthcare AI platform by Enigma Health, automates hospital administrative work. At KK Women's and Children's Hospital and PRISM1, 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.

  4. 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.

  5. 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. TRUST2, 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.

  1. Enigma, ELVF-FM and TRUST offer a glimpse of how we can harness the power of AI while remaining trusted.

  2. 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.

  3. 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

  1. Yet even the most sophisticated technology and robust governance frameworks cannot succeed in isolation. Healthcare transformation requires collective effort and shared expertise.

  2. 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.

  3. Today, I am glad to have witnessed the two MOU signings between Enigma Health and Roche as well as Enigma Health and ST Engineering.

  4. The two MOUs exemplify our collaborative approach to healthcare innovation.

  5. 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.

  6. The partnership between Enigma Health and ST Engineering will make healthcare innovation more accessible to those who understand patient needs best.

  7. 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.

  8. Thank you for your contributions to this symposium, and for being part of Singapore’s journey to build better healthcare for generations to come.

  9. I truly believe that together we can build a healthier future for all. Have a good day ahead.

1SingHealth Duke-NUS Institute of Precision Medicine

2Trusted Research and Real World Data Utilisation and Sharing Tech

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