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+<div class="sc-cmRAlD dkqmWS"><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-jgvlka jFuPjz"><div class="sc-gzqKSP ktvwwo"><div style="min-height: 80px;"><div class="sc-etVRix jqYJaa sc-bMmLMY ZURWJ"><p>The Data set consists of 1200 records of Cardiovascular ECGs where each of the 300 records belongs to one ailment, in such a way 4 ailments have been considered. The original signals are taken from the MIT-BIH physio-net Database. One ailment is the MIT-BIH Arrhythmia Database, the other is BIDMC Congestive Heart Failure Database and MIT-BIH Atrial Fibrillation Database and finally MIT-BIH Normal Sinus Rhythm Database. From these four databases, ECG records have been segmented at 4120 samples each forming 300 signals. They are normalized with mentioned gain for each database and are preprocessed with bandpass filters. MODWPT technique was used to obtain 54 features that are given as columns in .csv file that is uploaded here. So the file has 1200 x 54 size records.<br>
+Note:: Missing values have to be handled according to your application.</p>
+<p><strong>ACKNOWLEDGEMENT</strong><br>
+Please credit the authors if you use this dataset file in your research.</p>
+<p>Citation:</p>
+<ol>
+<li><p>Alekhya, L., and P. Rajesh Kumar, "A new approach to detect cardiovascular diseases using ECG scalograms and ML-based CNN algorithm." Mar 20, 2023. International Journal of Computational Vision and Robotics/Inderscience publishers. <br>
+DOI: 10.1504/IJCVR.2022.10051429 <br>
+Link: <a rel="noreferrer nofollow" aria-label="https://www.inderscience.com/info/ingeneral/forthcoming.php?jcode=IJCVR (opens in a new tab)" target="_blank" href="https://www.inderscience.com/info/ingeneral/forthcoming.php?jcode=IJCVR">https://www.inderscience.com/info/ingeneral/forthcoming.php?jcode=IJCVR</a></p></li>
+<li><p>Alekhya, L., and P. Rajesh Kumar. "A Novel Application for Autonomous Detection of Cardiac Ailments using ECG <br>
+Scalograms with Alex Net Convolution Neural Network." Design Engineering (2021): 13176-13189.<br>
+Link: <a rel="noreferrer nofollow" aria-label="http://www.thedesignengineering.com/index.php/DE/article/view/6434 (opens in a new tab)" target="_blank" href="http://www.thedesignengineering.com/index.php/DE/article/view/6434">http://www.thedesignengineering.com/index.php/DE/article/view/6434</a></p></li>
+<li><p>Autonomous Detection of Cardiac Ailments using Long-short term Memory Model based on Electrocardiogram signals, L. Alekhya, P. Rajesh Kumar, A. Venkata Sriram<br>
+DOI: 10.14704/nq.2022.20.7.NQ33431. Pages: 3509 - 3518.<br>
+Link: <a rel="noreferrer nofollow" aria-label="https://www.neuroquantology.com/open-access/Autonomous+Detection+of+Cardiac+Ailments+using+Longshort+term+Memory+Model+based+on+Electrocardiogram+signals_5781/ (opens in a new tab)" target="_blank" href="https://www.neuroquantology.com/open-access/Autonomous+Detection+of+Cardiac+Ailments+using+Longshort+term+Memory+Model+based+on+Electrocardiogram+signals_5781/">https://www.neuroquantology.com/open-access/Autonomous+Detection+of+Cardiac+Ailments+using+Longshort+term+Memory+Model+based+on+Electrocardiogram+signals_5781/</a></p></li>
+<li><p>Autonomous Detection of Cardia Ailments diagnosed by Electrocardiogram using various Supervised Machine Learning AlgorithmsAutonomous Detection of Cardia Ailments diagnosed by Electrocardiogram using various Supervised Machine Learning Algorithms<br>
+AMA, Agricultural Mechanization in Asia, Africa and Latin America (ISSN: 00845841) · Sep 18, 2021.<br>
+Link: <a rel="noreferrer nofollow" aria-label="https://www.shin-norinco.com/article/autonomous-detection-of-cardia-ailments-diagnosed-by-electrocardiogram-using-various-supervised-machine-learning-algorithms (opens in a new tab)" target="_blank" href="https://www.shin-norinco.com/article/autonomous-detection-of-cardia-ailments-diagnosed-by-electrocardiogram-using-various-supervised-machine-learning-algorithms">https://www.shin-norinco.com/article/autonomous-detection-of-cardia-ailments-diagnosed-by-electrocardiogram-using-various-supervised-machine-learning-algorithms</a></p></li>
+<li><p>L Alekhya, P Rajesh Kumar, “Maximal Overlap Discrete Wavelet Packet Transform Based Characteristic waves detection in Electrocardiogram of Cardiovascular Diseases”, INTERNATIONAL JOURNAL OF SPECIAL EDUCATION, vol 36 (1), pp 51-61, 2021.</p></li>
+</ol>
+<p><strong>License</strong><br>
+License was not specified at the source, yet access to the data is public and a citation was requested.</p></div></div></div>
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