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Artificial Intelligence for Detecting Preterm Uterine Activ..:

, In: 2015 IEEE International Conference on Computer and Information Technology; Ubiquitous Computing and Communications; Dependable, Autonomic and Secure Computing; Pervasive Intelligence and Computing,

Idowu, Ibrahim Olatunji ; Fergus, Paul ; Hussain, Abir... - p. 215-220 , 2015

Link: https://doi.org/10.1109/CIT/IUCC/DASC/PICOM.2015.31

RT 
T1 <cTitle>2015 IEEE International Conference on Computer and Information Technology; Ubiquitous Computing and Communications; Dependable, Autonomic and Secure Computing; Pervasive Intelligence and Computing</cTitle>: T1 <Title>Artificial Intelligence for Detecting Preterm Uterine Activity in Gynecology and Obstetric Care</Title>

UL https://suche.suub.uni-bremen.de/peid=ieee-7363073&Exemplar=1&LAN=DE
				
A1 Idowu, Ibrahim Olatunji
A1 Fergus, Paul
A1 Hussain, Abir
A1 Dobbins, Chelsea
A1 Khalaf, Mohammed
A1 Casana Eslava, Raul V.
A1 Keight, Robert
YR 2015
K1 Vegetation
K1 Feature extraction
K1 Pregnancy
K1 Pediatrics
K1 Machine learning algorithms
K1 Classification algorithms
K1 Databases
K1 Electrohysterography(EHG)
K1 Random Forest
K1 Preterm Delivery
K1 Term Delivery
K1 Classification
K1 Rule-Base
K1 AUROC and Features extraction
K1 Wavelet Transform (WT)
K1 Fourier Transform (FT)
K1 Preterm Labour ( PTL)
K1 Power Spectral Density (PSD)
K1 Leave-one-out Cross-va
SP 215
OP 220
LK http://dx.doi.org/https://doi.org/10.1109/CIT/IUCC/DASC/PICOM.2015.31
DO https://doi.org/10.1109/CIT/IUCC/DASC/PICOM.2015.31
SF ELIB - SuUB Bremen

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