Hosted at FoMPHN UGM, the Networking Session convened stakeholders from UGM and Sardjito Hospital (Indonesia), Bach Mai Hospital (Vietnam), and LDTRC MDX (The UK) to explore data-sharing opportunities and digital twin model development for stroke prediction and early intervention. Key discussion points included:
- The potential of sharing real-world hospital data (e.g., from Sardjito Hospital) with appropriate ethical clearance and de-identification for developing AI models
- Integrating stroke datasets from the UK, Indonesia, and Vietnam to enhance generalizability and model accuracy
- Leveraging AI-enabled tools such as breath analysis systems (used for COVID-19 and TB) for other diagnostic applications
- Investigating the use of an MoH-certified AI breath analysis tool, commercially deployed for COVID-19 developed by UGM team as a potential screening solution for other diseases.
- Exploring the opportunity to use real-time monitoring via wearable devices
- Supporting the establishment of a Mini Lab for Digital Twin Stroke Care in Indonesia
- Promoting applications for the London Digital Twin Research Fellowship, open to international researchers interested in AI for health (https://dt.mdx.ac.uk)
The session concluded with a shared commitment to building a Mini Lab Digital Twin for Stroke Care at UGM, serving as a regional hub for model testing, capacity-building, and data integration and fostering collaboration with Sardjito Hospital Stroke team to support clinical validation. The session highlighted shared priorities and affirmed the value of transnational collaboration for building scalable, evidence-based AI applications in health.
Leave a Reply