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


Subject Area

Health and Medicine

Associated Tasks


Feature Type


# Instances


# Features


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?


Variables Table

Variable NameRoleTypeDemographicDescriptionUnitsMissing Values

0 to 10 of 23

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)

Papers Citing this Dataset

A Differential Privacy Mechanism Design Under Matrix-Valued Query

By Thee Chanyaswad, Alex Dytso, H. Poor, Prateek Mittal. 2018

Published in ArXiv.

MVG Mechanism: Differential Privacy under Matrix-Valued Query

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).

The TreeRank Tournament algorithm for multipartite ranking

By Stéphan Clémençon, Sylvain Robbiano. 2015

Published in Journal of Nonparametric Statistics.

Finding reproducible cluster partitions for the k-means algorithm

By Paulo Lisboa, Terence Etchells, Ian Jarman, Simon Chambers. 2013

Published in BMC bioinformatics.

Ranking data with ordinal labels: optimality and pairwise aggregation

By Stéphan Clémençon, Sylvain Robbiano, Nicolas Vayatis. 2012

Published in Machine Learning.

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5 citations


D. Campos

J. Bernardes


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