Change-point detection for monitoring clinical decision support systems with a multi-process dynamic linear model

A clinical decision support system and its components may malfunction due to different reasons. The objective of this work is to develop computational methods that can help us to monitor the system and assure its proper operation by promptly detecting and analyzing changes in its behavior. We develo...

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Bibliographic Details
Published in:2017 IEEE International Conference on Bioinformatics and Biomedicine (BIBM) 2017-11, Vol.2017, p.569-572
Main Authors: Liu, Siqi, Wright, Adam, Sittig, Dean F., Hauskrecht, Milos
Format: Article
Language:English
Subjects:
Covariance matrices
Data models
Decision support systems
Delays
Monitoring
Real-time systems
Time series analysis
Online Access:Get full text
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Summary:A clinical decision support system and its components may malfunction due to different reasons. The objective of this work is to develop computational methods that can help us to monitor the system and assure its proper operation by promptly detecting and analyzing changes in its behavior. We develop a new change-point detection method using the Multi-Process Dynamic Linear Model. The experiments on real and simulated data show that our method outperforms existing change-point detection methods, leading to higher accuracy and shorter delay in the detection.
ISSN:2156-1125
DOI:10.1109/BIBM.2017.8217712