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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.

Nurse monitoring vital signs in intensive care unit

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)

Project partners

Universitätsspital Zürich / 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