心律失常数据集

Original Owners of Database: 1. H. Altay Guvenir, PhD., Bilkent University, Department of Computer Engineering and Information Science, 06533 Ankara, Turkey Phone: [phone] Email: guvenir '@' cs.bilkent.edu.tr 2. Burak Acar, M.S., Bilkent University, EE Eng. Dept. 06533 Ankara, Turkey Email: buraka '@' ee.bilkent.edu.tr 3. Haldun Muderrisoglu, M.D., Ph.D., Baskent University, School of Medicine Ankara, Turkey Donor: H. Altay Guvenir Bilkent University, Department of Computer Engineering and Information Science, 06533 Ankara, Turkey Phone: [phone] Email: guvenir '@' cs.bilkent.edu.tr Data Set 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. Attribute 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 Relevant Papers: H. Altay Guvenir, Burak Acar, Gulsen Demiroz, Ayhan Cekin "A Supervised Machine Learning Algorithm for Arrhythmia Analysis." Proceedings of the Computers in Cardiology Conference, Lund, Sweden, 1997. [Web Link] Papers That Cite This Data Set1: Krista Lagus and Esa Alhoniemi and Jeremias Seppa and Antti Honkela and Arno Wagner. INDEPENDENT VARIABLE GROUP ANALYSIS IN LEARNING COMPACT REPRESENTATIONS FOR DATA. Neural Networks Research Centre, Helsinki University of Technology. [View Context]. Gisele L. Pappa and Alex Alves Freitas and Celso A A Kaestner. AMultiobjective Genetic Algorithm for Attribute Selection. Computing Laboratory Pontificia Universidade Catolica do Parana University of Kent at Canterbury. [View Context]. Shay Cohen and Eytan Ruppin and Gideon Dror. Feature Selection Based on the Shapley Value. School of Computer Sciences Tel-Aviv University. [View Context]. Citation Request: Please refer to the Machine Learning Repository's citation policy