Output details
11 - Computer Science and Informatics
Middlesex University
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Article title
A MIXTURE MODEL CLASSIFIER AND ITS APPLICATION ON THE BIOMEDICAL TIME SERIES
Type
D - Journal article
Title of journal
Applied Artificial Intelligence
Article number
-
Volume number
26
Issue number
6
First page of article
588
ISSN of journal
1087-6545
Year of publication
2012
Number of additional authors
6
Additional information
<22>It is critical that a cardiac arrest patient suffering ventricular fibrillation (VF) is immediately treated by paramedics on site. This work presents a methodology based on the mixture model to classify the real ECG time series (VF data), in order to help paramedics to predict the efficiency of emergent treatment in the real time. It improves the results of our former work, which was supported by an EPSRC grant. This new work achieves the highest overall classification rate available so far, signifying that it possesses the highest prediction accuracy. It was a collaborative work between Norwegian and British scientists.
Interdisciplinary
-
Cross-referral requested
-
Research group
None
Citation count
0
Proposed double-weighted
No
Double-weighted statement
-
Reserve for a double-weighted output
No
Non-English
No
English abstract
-
