Harnessing digital twins for healthcare - Cerebrovascular Autoregulation in Critical Care (NeuroVascTwin)
We will explore the concept of Digital Twin in Healthcare to virtually reproduce patient-specific pathophysiological systems.
Description
We explore the concept of Digital Twin in Healthcare to virtually reproduce patient-specific pathophysiological systems. We will combine data-driven and model-driven approaches using data assimilation techniques and physics-informed machine learning, and exemplify them with clinical cases. Specifically, we implement a digital twin in a neurocritical care setting to infer the functional state of cerebrovascular autoregulation.
Key data
Projectlead
Project team
Ayla Durrer, Dr. Radoslava Svihrová, Prof. Dr. Emanuela Keller (Universitätsspital Zürich USZ)
Project partners
Universitätsspital Zürich USZ / Neurocritical Care Unit
Project status
ongoing, started 02/2026
Institute/Centre
Institute of Computational Life Sciences (ICLS)
Funding partner
Digitalisierungsinitiative der Zürcher Hochschulen DIZH / DIZH Fellowship 2024
Project budget
200'000 CHF
Further documents and links
School of Life Sciences and Facility Management
Schloss
8820 Wädenswil