Real-time prognosis of ICU physiological data streams

Author

Sow, Daby ; Biem, Alain ; Sun, Jimeng ; Hu, Jianying ; Ebadollahi, Shahram

Author_Institution

IBM T.J. Watson Res. Center, New York, NY, USA

fYear

2010

fDate

Aug. 31 2010-Sept. 4 2010

Firstpage

6785

Lastpage

6788

Abstract

This paper presents a system capable of predicting in real-time the evolution of Intensive Care Unit (ICU) physiological patient data streams. It leverages a state of the art stream computing platform to host analytics capable of making such prognosis in real time. The focus is on online algorithms that do not require a training phase. We use Fading-Memory Polynomial filters on the frequency domain to predict windows of ICU data streams. We report on both the system and the performance of this approach when applied to traces of more than 1500 ICU patients obtained from the MIMIC-II database.

Keywords

medical computing; patient care; ICU physiological data streams; MIMIC-II database; art stream computing platform; fading-memory polynomial filters; frequency domain; intensive care unit; online algorithms; real-time prognosis; Biomedical monitoring; Error analysis; Forecasting; Frequency domain analysis; Monitoring; Real time systems; Time domain analysis; Algorithms; Databases, Factual; Humans; Intensive Care Units;

fLanguage

English

Publisher

ieee

Conference_Titel

Engineering in Medicine and Biology Society (EMBC), 2010 Annual International Conference of the IEEE

Conference_Location

Buenos Aires

ISSN

1557-170X

Print_ISBN

978-1-4244-4123-5

Type

conf

DOI

10.1109/IEMBS.2010.5625983

Filename

5625983