The following day, the Network hosted a hybrid workshop under the Visiting Professor Program FoMPHN 2025 featuring Prof. Huan X. Nguyen, Director of the London Digital Twin Research Centre, Middlesex University London. His lecture, “StrokeDT: Early Intervention for Minor Stroke Patients in Vietnam and Indonesia using Digital Twinning,” showcased how digital twins can personalize stroke care through real-time prediction, simulation, and tailored treatment planning. Drawing from ongoing studies in Vietnam, he demonstrated how digital twins could help anticipate early neurological deterioration, optimize interventions like thrombolysis and thrombectomy, and enhance post-stroke rehabilitation. This was followed by a talk from Dr. Lutfan Lazuardi, who emphasized the growing burden of stroke in Indonesia and highlighted the need for AI and digital twin technologies to enable early prediction, real-time simulation, and cost-effective policy development. Dr. Lazuardi called for cross-sectoral collaboration to ensure innovation is inclusive, impactful, and grounded in local health system needs.
The workshop also featured two panel sessions:
Panel 1 – “Introduction to Stroke Management: Current Challenges & Future Directions”, moderated by Dr. Farida Niken Astari Nugroho Hati (Neurologist, UGM Academic Hospital), focused on national and regional approaches to stroke care.
- Setiyo Harini, S.K.M., M.Kes (Yogyakarta Provincial Health Office) presented the current stroke burden and public health strategies in the region.
- Dr. Rizaldi Pinzon (Bethesda Hospital Yogyakarta) introduced key stroke management quality indicators aligned with national and AHA/ASA guidelines.
- Dr. Lisda Amalia, Sp.S(K) (PERDOSNI – UNPAD) outlined stroke emergency protocols, including Code Stroke pathways.
- Phan Ha Quan, MSc, BSNT (Bach Mai Stroke Center, Vietnam) shared Vietnam’s experience in expanding stroke-ready hospitals and improving EMS coordination.
Panel 2 – “Opportunities to Use Data Science to Improve Stroke Care and Research”, moderated by Dr. Annisa Ristya Rahmanti (FoMPHN UGM), showcased real-world AI applications and predictive modeling for stroke.
- Dr. Bagas Suryo Bintoro (FoMPHN UGM) emphasized the role of co-designed digital health tools tailored to user needs.
- M. Solihuddin Muhtar, MBA (TMU, Taiwan) shared lessons from using EMR data for stroke prediction and AI development.
- Dr. Afiahayati (Dept. of Computer Science, UGM) discussed explainable machine learning using big data from the academic health system.
- Dr. Cong Minh Tran (University of Oxford) presented predictive modeling of early neurological deterioration in acute ischemic stroke.
- Hanifah Wulandari, MPH (Health Transformation Bureau, UGM) explored the use of DaSK and integrated health data for care quality and research improvement.
These sessions highlighted the need for scalable, data-driven innovations and underscored the value of interdisciplinary, cross-country collaboration to enhance stroke care outcomes.
Acknowledgment: These activities were jointly funded by the 2025 Visiting Professor Guest Lecture (VPGL) Grant from the Faculty of Medicine, Public Health, and Nursing at Universitas Gadjah Mada (UGM) and by the DTStroke Care Network through the Academy of Medical Sciences Grant and the British Council ISFP Project Grant.
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