Intrapartum fetal heart rate classification from trajectory in Sparse SVM feature space
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21730%2F15%3A00239724" target="_blank" >RIV/68407700:21730/15:00239724 - isvavai.cz</a>
Result on the web
<a href="http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=7318861&newsearch=true&queryText=%20Intrapartum%20fetal%20heart%20rate%20classification%20from%20trajectory%20in%20Sparse%20SVM%20feature%20spac" target="_blank" >http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=7318861&newsearch=true&queryText=%20Intrapartum%20fetal%20heart%20rate%20classification%20from%20trajectory%20in%20Sparse%20SVM%20feature%20spac</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/EMBC.2015.7318861" target="_blank" >10.1109/EMBC.2015.7318861</a>
Alternative languages
Result language
angličtina
Original language name
Intrapartum fetal heart rate classification from trajectory in Sparse SVM feature space
Original language description
Intrapartum fetal heart rate (FHR) constitutes a prominent source of information for the assessment of fetal reactions to stress events during delivery. Yet, early detection of fetal acidosis remains a challenging signal processing task. The originalityof the present contribution are three-fold: multiscale representations and wavelet leader based multifractal analysis are used to quantify FHR variability ; Supervised classification is achieved by means of Sparse-SVM that aim jointly to achieve optimaldetection performance and to select relevant features in a multivariate setting ; Trajectories in the feature space accounting for the evolution along time of features while labor progresses are involved in the construction of indices quantifying fetal health. The classification performance permitted by this combination of tools are quantified on a intrapartum FHR large database (~ 1250 subjects) collected at a French academic public hospital.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
JC - Computer hardware and software
OECD FORD branch
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Result continuities
Project
<a href="/en/project/NT11124" target="_blank" >NT11124: Impact of Cardiotocography evaluation by means of artificial inteligence on perinatal care</a><br>
Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2015
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
IEEE EMBC 2015 Proceedings (Milano)
ISBN
9781424492718
ISSN
1557-170X
e-ISSN
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Number of pages
4
Pages from-to
2335-2338
Publisher name
IEEE
Place of publication
Milano
Event location
Milano
Event date
Aug 25, 2015
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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