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Publications by MIG

2018-08-23 · The UCI Machine Learning Repository Cardiotocography dataset contains 2126 automatically processed cardiotocograms with 21 attributes. The two-way classification of the dataset as 10-class morphological patterns and 3-class fetal status was done by three expert obstetricians. The 10-class classification was attempted in this project. This article gives a summary about the cardiotocography dataset and how to do an simple EDA on it. The full R-script is provided at the end of the article.

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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. The features obtained from different origins, such as morphological, linear, nonlinear, time-frequency and image-based time-frequency domains are used as the inputs to classifiers. 2020-06-19 · Training Dataset Count: 620 Test Dataset Count: 148. Machine learning Model Building.

95. 27 Mar 2018 The dataset belongs to the Cardiotocography and it has the measurements of FHR and uterine contraction (UC) features on CTG classified by  7 Feb 2018 this code is written by "Omid Ghahary" to read all data from "The CTU-UHB Intrapartum Cardiotocography Database" located in  7 Oct 2014 We compared the outcomes for this combined oximetry and CTG, with outcomes where only the CTG had been used, or a combination of CTG  Classifier using publicly available Cardiotocography (CTG) dataset from INDEX TERMS Cardiotocography dataset, Dimensionality Reduction, Feature  23 Jul 2018 Interested in learning how to use JavaScript in the browser? In the last episode of Coding TensorFlow, we showed you a very basic ML  m (20 projection angles).

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This modality is also widely used to record fetal heart rate and uterine activity. 2021-04-04 · Cardiotocography-classification-with-Svm-and-Mlp This project compares the classification accuracy of SVM and Mlp on cardiotocography dataset. For the purpose of this project,we added suspicious and pathologic classes and created a new variable as a target value. In this section, we'll be using the Cardiotocography (CTG) dataset located at https://archive.ics.uci.edu/ml/datasets/cardiotocography.

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The original Cardiotocography (Cardio) dataset from UCI machine learning repository consists of measurements of fetal heart rate (FHR) and uterine contraction (UC) features on cardiotocograms classified by expert obstetricians. This is a classification dataset, where the classes are normal, suspect, and pathologic.

Principal Component Table 3: Evaluation result for cardiotocography dataset.
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For the purpose of this project,we added suspicious and pathologic classes and created a new variable as a target value. In this section, we'll be using the Cardiotocography (CTG) dataset located at https://archive.ics.uci.edu/ml/datasets/cardiotocography. It has 23 attributes, 2 of which are two different classifications of the same samples, CLASS (1 to 10) and NSP (1 to 3). Downloading the Dataset ¶ Cardiotocography [2] is common medical devices; many re-searches analyze datasets to achieve improved accuracy in diagnosing the state of fetal heart rate under uncertain situa-tions. The device produces a simultaneous recording and traces patterns of the FHR and the UC during pregnancy period and before delivery. CTG Data S et has 2126 different fetal CTG signal recordings comprised of 23 real features. Data is two target class description that are based on fetal hearth rate and morphology pattern.

Gå till. Epidemiology (Chapter  Abstract: The dataset consists of measurements of fetal heart rate (FHR) and uterine contraction (UC) features on cardiotocograms classified by expert obstetricians. The original Cardiotocography (Cardio) dataset from UCI machine learning repository consists of measurements of fetal heart rate (FHR) and uterine contraction (UC) features on cardiotocograms classified by expert obstetricians. This is a classification dataset, where the classes are normal, suspect, and pathologic. The dataset consists of measurements of fetal heart rate (FHR) and uterine contraction (UC) features on cardiotocograms classified by expert obstetricians.
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Features of each dataset used in this work. Data Set. 1 Aug 2015 Cardiotocography (CTG) is used as a technique of measuring fetal The dataset contains 1831 instances with 21 attributes, examined by  data sets. The selected features were used to construct classification models and their predictive https://archive.ics.uci.edu/ml/datasets/Cardiotocography. 95. 27 Mar 2018 The dataset belongs to the Cardiotocography and it has the measurements of FHR and uterine contraction (UC) features on CTG classified by  7 Feb 2018 this code is written by "Omid Ghahary" to read all data from "The CTU-UHB Intrapartum Cardiotocography Database" located in  7 Oct 2014 We compared the outcomes for this combined oximetry and CTG, with outcomes where only the CTG had been used, or a combination of CTG  Classifier using publicly available Cardiotocography (CTG) dataset from INDEX TERMS Cardiotocography dataset, Dimensionality Reduction, Feature  23 Jul 2018 Interested in learning how to use JavaScript in the browser?

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. Source: The dataset also reports classification of each deceleration as early, late, variable or prolonged, in relation to the presence of a uterine contraction. Annotations were obtained by an expert gynecologist with the support of CTG Analyzer, a dedicated software application for automatic analysis of digital CTG recordings. Neural Network in classifying cardiotocography dataset.
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Publications by MIG

The foremost motive of monitoring is to detect the fetal hypoxia at early stage. This modality is also widely used to record fetal heart rate and uterine activity. 2021-04-04 · Cardiotocography-classification-with-Svm-and-Mlp This project compares the classification accuracy of SVM and Mlp on cardiotocography dataset. For the purpose of this project,we added suspicious and pathologic classes and created a new variable as a target value. In this section, we'll be using the Cardiotocography (CTG) dataset located at https://archive.ics.uci.edu/ml/datasets/cardiotocography. It has 23 attributes, 2 of which are two different classifications of the same samples, CLASS (1 to 10) and NSP (1 to 3).