NDLI: Discovering shared dynamics in physiological signals: Application to patient monitoring in ICU

Content Provider	IEEE Xplore Digital Library
Author	Lehman, L.H. Nemati, S. Adams, R.P. Mark, R.G.
Copyright Year	2012
Description	Author affiliation: Massachusetts Inst. of Technol., Cambridge, MA, USA (Lehman, L.H.; Nemati, S.; Mark, R.G.) \|\| Sch. of Eng. & Appl. Sci., Harvard Univ., Cambridge, MA, USA (Adams, R.P.)
Abstract	Modern clinical databases include time series of vital signs, which are often recorded continuously during a hospital stay. Over several days, these recordings may yield many thousands of samples. In this work, we explore the feasibility of characterizing the “state of health” of a patient using the physiological dynamics inferred from these time series. The ultimate objective is to assist clinicians in allocating resources to high-risk patients. We hypothesize that “similar” patients exhibit similar dynamics and the properties and duration of these states are indicative of health and disease. We use Bayesian nonparametric machine learning methods to discover shared dynamics in patients' blood pressure (BP) time series. Each such “dynamic” captures a distinct pattern of evolution of BP and is possibly recurrent within the same time series and shared across multiple patients. Next, we examine the utility of this low-dimensional representation of BP time series for predicting mortality in patients. Our results are based on an intensive care unit (ICU) cohort of 480 patients (with 16% mortality) and indicate that the dynamics of time series of vital signs can be an independent useful predictor of outcome in ICU.
Sponsorship	IEEE Eng. Medicine Biol. Soc.
Starting Page	5939
Ending Page	5942
File Size	700993
Page Count	4
File Format	PDF
ISBN	9781424441198
ISSN	1557170X
e-ISBN	9781457717871
DOI	10.1109/EMBC.2012.6347346
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-08-28
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Time series analysis Hospitals Biomedical monitoring Bayesian methods Sociology Logistics
Content Type	Text
Resource Type	Article
Subject	Signal Processing Biomedical Engineering Health Informatics Computer Vision and Pattern Recognition

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

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