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+<div class="sc-jegwdG lhLRCf"><div class="sc-UEtKG dGqiYy sc-flttKd cguEtd"><div class="sc-fqwslf gsqkEc"><div class="sc-cBQMlg kAHhUk"><h2 class="sc-dcKlJK sc-cVttbi gqEuPW ksnHgj">About Dataset</h2></div></div></div><div class="sc-davvxH eCVTlP"><div class="sc-jCNfQM ikRdXB"><div style="min-height: 80px;"><div class="sc-etVRix jqYJaa sc-gVIFzB gQKGyV"><h1>Context</h1>
+<h1>ECG Heartbeat Categorization Dataset</h1>
+<h2>Abstract</h2>
+<p>This dataset is composed of two collections of heartbeat signals derived from two famous datasets in heartbeat classification, <a rel="noreferrer nofollow" aria-label="the MIT-BIH Arrhythmia Dataset (opens in a new tab)" target="_blank" href="https://www.physionet.org/physiobank/database/mitdb/">the MIT-BIH Arrhythmia Dataset</a> and <a rel="noreferrer nofollow" aria-label="The PTB Diagnostic ECG Database (opens in a new tab)" target="_blank" href="https://www.physionet.org/physiobank/database/ptbdb/">The PTB Diagnostic ECG Database</a>. The number of samples in both collections is large enough for training a deep neural network. </p>
+<p>This dataset has been used in exploring heartbeat classification using deep neural network architectures, and observing some of the capabilities of transfer learning on it. The signals correspond to electrocardiogram (ECG) shapes of heartbeats for the normal case and the cases affected by different arrhythmias and myocardial infarction. These signals are preprocessed and segmented, with each segment corresponding to a heartbeat.</p>
+<h2>Content</h2>
+<h3>Arrhythmia Dataset</h3>
+<ul>
+    <li> Number of Samples: 109446</li>
+    <li> Number of Categories: 5</li>
+    <li> Sampling Frequency: 125Hz</li>
+    <li> Data Source: Physionet's MIT-BIH Arrhythmia Dataset</li>
+    <li> Classes: ['N': 0, 'S': 1, 'V': 2, 'F': 3, 'Q': 4]</li>
+</ul>
+<h3>The PTB Diagnostic ECG Database</h3>
+<ul>
+    <li> Number of Samples: 14552</li>
+    <li> Number of Categories: 2</li>
+    <li> Sampling Frequency: 125Hz</li>
+    <li> Data Source: Physionet's PTB Diagnostic Database</li>
+</ul>
+<p><strong>Remark</strong>: <em>All the samples are cropped, downsampled and padded with zeroes if necessary to the fixed dimension of 188</em>.</p>
+<h2>Data Files</h2>
+<p>This dataset consists of a series of CSV files. Each of these CSV files contain a matrix, with each row representing an example in that portion of the dataset. The final element of each row denotes the class to which that example belongs.</p>
+<h2>Acknowledgements</h2>
+<p>Mohammad Kachuee, Shayan Fazeli, and Majid Sarrafzadeh. "ECG Heartbeat Classification: A Deep Transferable Representation." <a rel="noreferrer nofollow" aria-label="<em>arXiv preprint arXiv:1805.00794 (2018)</em> (opens in a new tab)" target="_blank" href="https://arxiv.org/abs/1805.00794"><em>arXiv preprint arXiv:1805.00794 (2018)</em></a>.</p>
+<h1>Inspiration</h1>
+<p>Can you identify myocardial infarction?</p></div></div></div>
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