Arrhythmia

Donated on 12/31/1997

Distinguish between the presence and absence of cardiac arrhythmia and classify it in one of the 16 groups.

Dataset Characteristics

Multivariate

Subject Area

Health and Medicine

Associated Tasks

Classification

Feature Type

Categorical, Integer, Real

# Instances

452

# Features

279

Dataset Information

Additional Information

This database contains 279 attributes, 206 of which are linear valued and the rest are nominal. Concerning the study of H. Altay Guvenir: "The aim is to distinguish between the presence and absence of cardiac arrhythmia and to classify it in one of the 16 groups. Class 01 refers to 'normal' ECG classes 02 to 15 refers to different classes of arrhythmia and class 16 refers to the rest of unclassified ones. For the time being, there exists a computer program that makes such a classification. However there are differences between the cardiolog's and the programs classification. Taking the cardiolog's as a gold standard we aim to minimise this difference by means of machine learning tools." The names and id numbers of the patients were recently removed from the database.

Has Missing Values?

Yes

Variables Table

Variable NameRoleTypeDemographicDescriptionUnitsMissing Values
Variable 1FeatureIntegerno
Variable 2FeatureIntegerno
Variable 3FeatureIntegerno
Variable 4FeatureIntegerno
Variable 5FeatureIntegerno
Variable 6FeatureIntegerno
Variable 7FeatureIntegerno
Variable 8FeatureIntegerno
Variable 9FeatureIntegerno
Variable 10FeatureIntegerno

0 to 10 of 280

Additional Variable Information

-- Complete attribute documentation: 1 Age: Age in years , linear 2 Sex: Sex (0 = male; 1 = female) , nominal 3 Height: Height in centimeters , linear 4 Weight: Weight in kilograms , linear 5 QRS duration: Average of QRS duration in msec., linear 6 P-R interval: Average duration between onset of P and Q waves in msec., linear 7 Q-T interval: Average duration between onset of Q and offset of T waves in msec., linear 8 T interval: Average duration of T wave in msec., linear 9 P interval: Average duration of P wave in msec., linear Vector angles in degrees on front plane of:, linear 10 QRS 11 T 12 P 13 QRST 14 J 15 Heart rate: Number of heart beats per minute ,linear Of channel DI: Average width, in msec., of: linear 16 Q wave 17 R wave 18 S wave 19 R' wave, small peak just after R 20 S' wave 21 Number of intrinsic deflections, linear 22 Existence of ragged R wave, nominal 23 Existence of diphasic derivation of R wave, nominal 24 Existence of ragged P wave, nominal 25 Existence of diphasic derivation of P wave, nominal 26 Existence of ragged T wave, nominal 27 Existence of diphasic derivation of T wave, nominal Of channel DII: 28 .. 39 (similar to 16 .. 27 of channel DI) Of channels DIII: 40 .. 51 Of channel AVR: 52 .. 63 Of channel AVL: 64 .. 75 Of channel AVF: 76 .. 87 Of channel V1: 88 .. 99 Of channel V2: 100 .. 111 Of channel V3: 112 .. 123 Of channel V4: 124 .. 135 Of channel V5: 136 .. 147 Of channel V6: 148 .. 159 Of channel DI: Amplitude , * 0.1 milivolt, of 160 JJ wave, linear 161 Q wave, linear 162 R wave, linear 163 S wave, linear 164 R' wave, linear 165 S' wave, linear 166 P wave, linear 167 T wave, linear 168 QRSA , Sum of areas of all segments divided by 10, ( Area= width * height / 2 ), linear 169 QRSTA = QRSA + 0.5 * width of T wave * 0.1 * height of T wave. (If T is diphasic then the bigger segment is considered), linear Of channel DII: 170 .. 179 Of channel DIII: 180 .. 189 Of channel AVR: 190 .. 199 Of channel AVL: 200 .. 209 Of channel AVF: 210 .. 219 Of channel V1: 220 .. 229 Of channel V2: 230 .. 239 Of channel V3: 240 .. 249 Of channel V4: 250 .. 259 Of channel V5: 260 .. 269 Of channel V6: 270 .. 279

Class Labels

Class code : Class : Number of instances: 01 Normal 245 02 Ischemic changes (Coronary Artery Disease) 44 03 Old Anterior Myocardial Infarction 15 04 Old Inferior Myocardial Infarction 15 05 Sinus tachycardy 13 06 Sinus bradycardy 25 07 Ventricular Premature Contraction (PVC) 3 08 Supraventricular Premature Contraction 2 09 Left bundle branch block 9 10 Right bundle branch block 50 11 1. degree AtrioVentricular block 0 12 2. degree AV block 0 13 3. degree AV block 0 14 Left ventricule hypertrophy 4 15 Atrial Fibrillation or Flutter 5 16 Others 22

Papers Citing this Dataset

A Fuzzy-Rough based Binary Shuffled Frog Leaping Algorithm for Feature Selection

By Javad Anaraki, Saeed Samet, Mahdi Eftekhari, Chang Ahn. 2018

Published in ArXiv.

Time Warp Invariant Dictionary Learning for Time Series Clustering: Application to Music Data Stream Analysis

By Saeed Yazdi, Ahlame Chouakria, Patrick Gallinari, Manuel Moussallam. 2018

Published in ECML/PKDD.

Application of the Variable Precision Rough Sets Model to Estimate the Outlier Probability of Each Element

By Francisco Pérez, José Berná-Martínez, Alberto Oliva, Miguel Ortega. 2018

Published in Complexity.

A Robust AUC Maximization Framework with Simultaneous Outlier Detection and Feature Selection for Positive-Unlabeled Classification

By Ke Ren, Haichuan Yang, Yu Zhao, Mingshan Xue, Hongyu Miao, Shuai Huang, Ji Liu. 2018

Published in ArXiv.

A comprehensive empirical comparison of hubness reduction in high-dimensional spaces

By Roman Feldbauer, Arthur Flexer. 2018

Published in Knowledge and Information Systems.

0 to 5 of 19

Reviews

There are no reviews for this dataset yet.

Login to Write a Review
Download
19 citations
36972 views

Creators

H. Guvenir

Burak Acar

Haldun Muderrisoglu

R. Quinlan

License

By using the UCI Machine Learning Repository, you acknowledge and accept the cookies and privacy practices used by the UCI Machine Learning Repository.

Read Policy