ICU Cockpit: a platform for collecting multimodal waveform data, AI-based computational disease modeling and real-time decision support in the intensive care unit. (13th May 2022)

• Record Type: Journal Article
• Authors: Boss, Jens Michael; Narula, Gagan; Straessle, Christian; Willms, Jan; Azzati, Jan; Brodbeck, Dominique; Luethy, Rahel; Suter, Susanne; Buehler, Christof; Muroi, Carl; Mack, David Jule; Seric, Marko; Baumann, Daniel; Keller, Emanuela
• Is Part Of: Journal of the American Medical Informatics Association. Volume 29:Number 7(2022)
• Page Start: 1286
• Page End: 1291
• Publication Date: 2022-05-13
• Subjects: clinical research data platform -- high resolution waveforms -- data dashboards -- livestream UI -- machine learning integration; Medical informatics -- Periodicals; Information Services -- Periodicals; Medical Informatics -- Periodicals; Médecine -- Informatique -- Périodiques; Informatica; Geneeskunde; Informatique médicale; Computer network resources; Electronic journals; 610.285
• DOI: 10.1093/jamia/ocac064
• Languages: English
• ISSNs: 1067-5027

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.