Forskning 2012 - Sahlgrenska Universitetssjukhuset - Yumpu

The dataset consists of measurements of fetal heart rate (FHR) and uterine contraction (UC) features on cardiotocograms classified by expert obstetricians. Source: Marques de SÃƒÂ¡, J.P., jpmdesa '@' ctg: Cardiotocography Data Set Description. A data set containing measurements of fetal heart rate and uterine contraction from cardiotocograms. This data set was Cardiotocography Data Set Classification with Extreme Learning Machine May 2018 Conference: International Conference on Advanced Technologies, Computer Engineering and Science (ICATCES’18) The CTGs were also classified by three expert obstetricians and a consensus classification label assigned to each of them. Classification was both with respect to a morphologic pattern (A, B, C. …) and to a fetal state (N, S, P). Therefore the dataset can be used either for 10-class or 3-class experiments. Acknowledgements.

The highD dataset is a new dataset of naturalistic vehicle trajectories recorded on German highways. Using a drone, typical limitations of established traffic data smartLoc: GNSS Dataset. Our datasets contain GNSS data from two sensors recorded during real-world urban driving scenarios. On the one hand a 1 Aug 2016 Stanford Drone Dataset.

The given dataset included 2126 instances of fetal cardiotocographic parameters.

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The set contained no missing features. The target labels for each of the data points were: 1) Morphological pattern: The data classified into 10 The Cardiotocography (CTG) dataset consisted of the measurement of Fetal Heart Rate (FHR) and Uterine Contraction (UC) features on Cardiotocograms data, used to evaluate maternal and fetal well-being during pregnancy and before delivery [4].

Institutioner vid LTH - Forskningsoutput - Lunds universitet

The efficiency of the proposed model was tested on the antenatal CTG dataset from the UCI repository. The WRF model achieved an average area under the receiver operating characteristic curve (ROC) of 0.99.

For the purpose of this project,we added suspicious and pathologic classes and created a new variable as a target value.
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The foremost motive of monitoring is to detect the fetal hypoxia at early stage.

Classification was both with respect to a morphologic pattern (A, B, C. …) and to a fetal state (N, S, P). Therefore the dataset can be used either for 10-class or 3-class experiments. Acknowledgements.
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NEONATAL COMPLICATIONS FOLLOWING BIRTH - CORE

Fergus P(1), Selvaraj M(2), Chalmers C(3). Author information: (1)Liverpool John Moores University, Faculty of Engineering and Technology, Data Science Research Centre, Department of Computer Science, Byron Street, Liverpool, L3 3AF, United Kingdom. A dataset containing LB,AC,FM23 variables of 2126 obejects. Datasets, functions and examples from the book: R Data Analysis-Methods and Application (in chinese)by Kuangnan Fang et al Dataset: H ere, we will build a model using Cardiotocography (Cardio) dataset, available in UCI machine learning repository, consists of measurements of fetal heart rate (FHR) and uterine contraction (UC). features on cardiotocograms classified by expert obstetricians have evaluated all the features and classified each example as normal, suspect, and pathologic for the attribute NSP. Cardiotocography (CTG) is a technical means of recording the fetal heartbeat and the uterine contractions during pregnancy.The machine used to perform the monitoring is called a cardiotocograph, more commonly known as an electronic fetal monitor (EFM). In this work two of the prominent dimensionality reduction techniques, Linear Discriminant Analysis (LDA) and Principal Component Analysis (PCA) are investigated on four popular Machine Learning (ML) algorithms, Decision Tree Induction, Support Vector Machine (SVM), Naive Bayes Classifier and Random Forest Classifier using publicly available Cardiotocography (CTG) dataset from University of Open Access Software for Cardiotocography Analysis (CTG-OAS) is developed to analyze fetal heart rate (FHR) signals. The software provides several tools to characterize the FHR signals.

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2010 : Geo-Magnetic field and WLAN dataset for indoor localisation from wristband and smartphone. Cardiotocography (CTG) is the most common non-invasive diagnostic technique to evaluate fetal well-being.

12 Nov 2019 Downloading the Dataset¶. To keep this notebook independant, we will download the CTG dataset within our code. If you've Comparative analysis of classification techniques using Cardiotocography dataset.