ICU Cockpit: a platform for collecting multimodal waveform data, AI-based computational disease modeling and real-time decision support in the intensive care unit

Author:

Boss Jens Michael1ORCID,Narula Gagan1,Straessle Christian1,Willms Jan1,Azzati Jan2,Brodbeck Dominique2,Luethy Rahel2ORCID,Suter Susanne3ORCID,Buehler Christof3,Muroi Carl1ORCID,Mack David Jule1,Seric Marko1,Baumann Daniel1,Keller Emanuela1

Affiliation:

1. Neurocritical Care Unit, Department of Neurosurgery and Institute of Intensive Care Medicine, University Hospital Zurich , Zurich, Switzerland

2. Institute for Medical Engineering and Medical Informatics, School of Life Sciences, University of Applied Sciences and Arts Northwestern Switzerland , Muttenz, Switzerland

3. Life Science and Physics, Supercomputing Systems AG , Zurich, Switzerland

Abstract

Abstract ICU Cockpit: a secure, fast, and scalable platform for collecting multimodal waveform data, online and historical data visualization, and online validation of algorithms in the intensive care unit. We present a network of software services that continuously stream waveforms from ICU beds to databases and a web-based user interface. Machine learning algorithms process the data streams and send outputs to the user interface. The architecture and capabilities of the platform are described. Since 2016, the platform has processed over 89 billion data points (N = 979 patients) from 200 signals (0.5–500 Hz) and laboratory analyses (once a day). We present an infrastructure-based framework for deploying and validating algorithms for critical care. The ICU Cockpit is a Big Data platform for critical care medicine, especially for multimodal waveform data. Uniquely, it allows algorithms to seamlessly integrate into the live data stream to produce clinical decision support and predictions in clinical practice.

Funder

ICU Cockpit research platform was supported by the Swiss National Science Foundation

IP-LS

Vontobel

Helmut Horten

Gebert-Rüf-

Herzog Egli-

Hasler-

USZ Foundations

Publisher

Oxford University Press (OUP)

Subject

Health Informatics

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