Cardiotocography
Donated on 9/6/2010
The dataset consists of measurements of fetal heart rate (FHR) and uterine contraction (UC) features on cardiotocograms classified by expert obstetricians.
Dataset Characteristics
Multivariate
Subject Area
Health and Medicine
Associated Tasks
Classification
Feature Type
Real
# Instances
2126
# Features
21
Dataset Information
Additional Information
2126 fetal cardiotocograms (CTGs) were automatically processed and the respective diagnostic features measured. 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.
Has Missing Values?
No
Variables Table
| Variable Name | Role | Type | Description | Units | Missing Values |
|---|---|---|---|---|---|
| LB | Feature | Integer | no | ||
| AC | Feature | Continuous | no | ||
| FM | Feature | Continuous | no | ||
| UC | Feature | Continuous | no | ||
| DL | Feature | Continuous | no | ||
| DS | Feature | Continuous | no | ||
| DP | Feature | Continuous | no | ||
| ASTV | Feature | Integer | no | ||
| MSTV | Feature | Continuous | no | ||
| ALTV | Feature | Integer | no |
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Additional Variable Information
LB - FHR baseline (beats per minute) AC - # of accelerations per second FM - # of fetal movements per second UC - # of uterine contractions per second DL - # of light decelerations per second DS - # of severe decelerations per second DP - # of prolongued decelerations per second ASTV - percentage of time with abnormal short term variability MSTV - mean value of short term variability ALTV - percentage of time with abnormal long term variability MLTV - mean value of long term variability Width - width of FHR histogram Min - minimum of FHR histogram Max - Maximum of FHR histogram Nmax - # of histogram peaks Nzeros - # of histogram zeros Mode - histogram mode Mean - histogram mean Median - histogram median Variance - histogram variance Tendency - histogram tendency CLASS - FHR pattern class code (1 to 10) NSP - fetal state class code (N=normal; S=suspect; P=pathologic)
Dataset Files
| File | Size |
|---|---|
| CTG.xls | 1.7 MB |
Papers Citing this Dataset
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By Thee Chanyaswad, Alex Dytso, H. Poor, Prateek Mittal. 2018
Published in ArXiv.
By Thee Chanyaswad, Alex Dytso, H. Poor, Prateek Mittal. 2018
Published in Thee Chanyaswad, Alex Dytso, H. Vincent Poor, and Prateek Mittal. 2018. MVG Mechanism: Differential Privacy under Matrix-Valued Query. In 2018 ACM SIGSAC Conference on Computer and Communications Security (CCS'18).
By Stéphan Clémençon, Sylvain Robbiano. 2015
Published in Journal of Nonparametric Statistics.
By Paulo Lisboa, Terence Etchells, Ian Jarman, Simon Chambers. 2013
Published in BMC bioinformatics.
By Stéphan Clémençon, Sylvain Robbiano, Nicolas Vayatis. 2012
Published in Machine Learning.
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pip install ucimlrepo
from ucimlrepo import fetch_ucirepo # fetch dataset cardiotocography = fetch_ucirepo(id=193) # data (as pandas dataframes) X = cardiotocography.data.features y = cardiotocography.data.targets # metadata print(cardiotocography.metadata) # variable information print(cardiotocography.variables)
Campos, D. & Bernardes, J. (2000). Cardiotocography [Dataset]. UCI Machine Learning Repository. https://doi.org/10.24432/C51S4N.
Creators
D. Campos
J. Bernardes
DOI
License
This dataset is licensed under a Creative Commons Attribution 4.0 International (CC BY 4.0) license.
This allows for the sharing and adaptation of the datasets for any purpose, provided that the appropriate credit is given.