Related references
Note: Only part of the references are listed.Use of artificial intelligence (AI) in the interpretation of intrapartum fetal heart rate (FHR) tracings: a systematic review and meta-analysis
Jacques Balayla et al.
ARCHIVES OF GYNECOLOGY AND OBSTETRICS (2019)
Person identification using ECG signal's symbolic representation and dynamic time warping adaptation
Leila Yousofvand et al.
SIGNAL IMAGE AND VIDEO PROCESSING (2019)
Sparse Support Vector Machine for Intrapartum Fetal Heart Rate Classification
Jiri Spilka et al.
IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS (2017)
Investigating pH based evaluation of fetal heart rate (FHR) recordings
George Georgoulas et al.
HEALTH AND TECHNOLOGY (2017)
Analysis of UV spectral bands using multidimensional scaling
J. A. Tenreiro Machado et al.
SIGNAL IMAGE AND VIDEO PROCESSING (2015)
Fetal Heart Rate Classification Using Generative Models
Shishir Dash et al.
IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING (2014)
Analysis of obstetricians' decision making on CTG recordings
Jiri Spilka et al.
JOURNAL OF BIOMEDICAL INFORMATICS (2014)
Open access intrapartum CTG database
Vaclav Chudacek et al.
BMC PREGNANCY AND CHILDBIRTH (2014)
Fetal state assessment using fuzzy analysis of fetal heart rate signals-Agreement with the neonatal outcome
Robert Czabanski et al.
BIOCYBERNETICS AND BIOMEDICAL ENGINEERING (2013)
Artificial neural networks applied to fetal monitoring in labour
Antoniya Georgieva et al.
NEURAL COMPUTING & APPLICATIONS (2013)
Prediction of fetal state from the cardiotocogram recordings using adaptive neuro-fuzzy inference systems
Hasan Ocak et al.
NEURAL COMPUTING & APPLICATIONS (2013)
Quantitative Assessment of Fetal Well-Being Through CTG Recordings: A New Parameter Based on Phase-Rectified Signal Average
Andrea Fanelli et al.
IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS (2013)
Using nonlinear features for fetal heart rate classification
J. Spilka et al.
BIOMEDICAL SIGNAL PROCESSING AND CONTROL (2012)
Electronic fetal heart rate monitoring and its relationship to neonatal and infant mortality in the United States
Han-Yang Chen et al.
AMERICAN JOURNAL OF OBSTETRICS AND GYNECOLOGY (2011)
Interobserver and intraobserver reliability of the NICHD 3-Tier Fetal Heart Rate Interpretation System
Sean C. Blackwell et al.
AMERICAN JOURNAL OF OBSTETRICS AND GYNECOLOGY (2011)
Predicting the Risk of Low-Fetal Birth Weight From Cardiotocographic Signals Using ANBLIR System With Deterministic Annealing and ε-Insensitive Learning
Robert Czabanski et al.
IEEE TRANSACTIONS ON INFORMATION TECHNOLOGY IN BIOMEDICINE (2010)
Combating the Small Sample Class Imbalance Problem Using Feature Selection
Mike Wasikowski et al.
IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING (2010)
Complexity analysis of the fetal heart rate variability: early identification of severe intrauterine growth-restricted fetuses
Manuela Ferrario et al.
MEDICAL & BIOLOGICAL ENGINEERING & COMPUTING (2009)
Invariant gait continuum based on the duty-factor
Preben Fihl et al.
SIGNAL IMAGE AND VIDEO PROCESSING (2009)
Experiencing SAX: a novel symbolic representation of time series
Jessica Lin et al.
DATA MINING AND KNOWLEDGE DISCOVERY (2007)
Predicting the risk of metabolic acidosis for newborns based on fetal heart rate signal classification using support vector machines
G Georgoulas et al.
IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING (2006)
Fetal electrocardiography in labor and neonatal outcome: Data from the Swedish randomized controlled trial on intrapartum fetal monitoring
H Noren et al.
AMERICAN JOURNAL OF OBSTETRICS AND GYNECOLOGY (2003)
A global geometric framework for nonlinear dimensionality reduction
JB Tenenbaum et al.
SCIENCE (2000)