{ "data_id": "5", "name": "arrhythmia", "exact_name": "arrhythmia", "version": 1, "version_label": "1", "description": "**Author**: H. Altay Guvenir, Burak Acar, Haldun Muderrisoglu \n**Source**: [UCI](https:\/\/archive.ics.uci.edu\/ml\/datasets\/arrhythmia) \n**Please cite**: [UCI](https:\/\/archive.ics.uci.edu\/ml\/citation_policy.html)\n\n**Cardiac Arrhythmia Database** \nThe aim is to determine the type of arrhythmia from the ECG recordings. This database contains 279 attributes, 206 of which are linear valued and the rest are nominal. \n\nConcerning 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 cardiologist's and the program's classification. Taking the cardiologist's as a gold standard we aim to minimize this difference by means of machine learning tools.\n \nThe names and id numbers of the patients were recently removed from the database.\n \n### Attribute Information \n \n 1 Age: Age in years , linear\n 2 Sex: Sex (0 = male; 1 = female) , nominal\n 3 Height: Height in centimeters , linear\n 4 Weight: Weight in kilograms , linear\n 5 QRS duration: Average of QRS duration in msec., linear\n 6 P-R interval: Average duration between onset of P and Q waves\n in msec., linear\n 7 Q-T interval: Average duration between onset of Q and offset\n of T waves in msec., linear\n 8 T interval: Average duration of T wave in msec., linear\n 9 P interval: Average duration of P wave in msec., linear\n Vector angles in degrees on front plane of:, linear\n 10 QRS\n 11 T\n 12 P\n 13 QRST\n 14 J\n 15 Heart rate: Number of heart beats per minute ,linear\n Of channel DI:\n Average width, in msec., of: linear\n 16 Q wave\n 17 R wave\n 18 S wave\n 19 R' wave, small peak just after R\n 20 S' wave\n 21 Number of intrinsic deflections, linear\n 22 Existence of ragged R wave, nominal\n 23 Existence of diphasic derivation of R wave, nominal\n 24 Existence of ragged P wave, nominal\n 25 Existence of diphasic derivation of P wave, nominal\n 26 Existence of ragged T wave, nominal\n 27 Existence of diphasic derivation of T wave, nominal\n Of channel DII: \n 28 .. 39 (similar to 16 .. 27 of channel DI)\n Of channels DIII:\n 40 .. 51\n Of channel AVR:\n 52 .. 63\n Of channel AVL:\n 64 .. 75\n Of channel AVF:\n 76 .. 87\n Of channel V1:\n 88 .. 99\n Of channel V2:\n 100 .. 111\n Of channel V3:\n 112 .. 123\n Of channel V4:\n 124 .. 135\n Of channel V5:\n 136 .. 147\n Of channel V6:\n 148 .. 159\n Of channel DI:\n Amplitude , * 0.1 milivolt, of\n 160 JJ wave, linear\n 161 Q wave, linear\n 162 R wave, linear\n 163 S wave, linear\n 164 R' wave, linear\n 165 S' wave, linear\n 166 P wave, linear\n 167 T wave, linear\n 168 QRSA , Sum of areas of all segments divided by 10,\n ( Area= width * height \/ 2 ), linear\n 169 QRSTA = QRSA + 0.5 * width of T wave * 0.1 * height of T\n wave. (If T is diphasic then the bigger segment is\n considered), linear\n Of channel DII:\n 170 .. 179\n Of channel DIII:\n 180 .. 189\n Of channel AVR:\n 190 .. 199\n Of channel AVL:\n 200 .. 209\n Of channel AVF:\n 210 .. 219\n Of channel V1:\n 220 .. 229\n Of channel V2:\n 230 .. 239\n Of channel V3:\n 240 .. 249\n Of channel V4:\n 250 .. 259\n Of channel V5:\n 260 .. 269\n Of channel V6:\n 270 .. 279\n \nClass code - class - number of instances:\n> \n 01 Normal 245\n 02 Ischemic changes (Coronary Artery Disease) 44\n 03 Old Anterior Myocardial Infarction 15\n 04 Old Inferior Myocardial Infarction 15\n 05 Sinus tachycardy 13\n 06 Sinus bradycardy 25\n 07 Ventricular Premature Contraction (PVC) 3\n 08 Supraventricular Premature Contraction 2\n 09 Left bundle branch block 9 \n 10 Right bundle branch block 50\n 11 1. degree AtrioVentricular block 0 \n 12 2. degree AV block 0\n 13 3. degree AV block 0\n 14 Left ventricule hypertrophy 4\n 15 Atrial Fibrillation or Flutter 5\n 16 Others 22", "format": "ARFF", "uploader": "Jan van Rijn", "uploader_id": 1, "visibility": "public", "creator": "H. Altay Guvenir,Burak Acar,Haldun Muderrisoglu", "contributor": null, "date": "2014-04-06 23:19:36", "update_comment": null, "last_update": "2014-04-06 23:19:36", "licence": "Public", "status": "active", "error_message": null, "url": "https:\/\/www.openml.org\/data\/download\/5\/dataset_5_arrhythmia.arff", "kaggle_url": null, "default_target_attribute": "class", "row_id_attribute": null, "ignore_attribute": null, "runs": 4473, "suggest": { "input": [ "arrhythmia", "The aim is to determine the type of arrhythmia from the ECG recordings. 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. 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