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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 tNtjD"><div style="min-height: 80px;"><div class="sc-etVRix jqYJaa sc-bMmLMY ZURWJ"><h1>About this dataset</h1> |
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<p>Cardiovascular diseases (CVDs) are the <strong>number 1 cause of death globally</strong>, taking an estimated <strong>17.9 million lives each year</strong>, which accounts for <strong>31% of all deaths worlwide</strong>.<br> |
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Heart failure is a common event caused by CVDs and this dataset contains 12 features that can be used to predict mortality by heart failure.</p> |
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<p>Most cardiovascular diseases can be prevented by addressing behavioural risk factors such as tobacco use, unhealthy diet and obesity, physical inactivity and harmful use of alcohol using population-wide strategies.</p> |
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<p>People with cardiovascular disease or who are at high cardiovascular risk (due to the presence of one or more risk factors such as hypertension, diabetes, hyperlipidaemia or already established disease) need <strong>early detection</strong> and management wherein a machine learning model can be of great help.</p> |
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<h1>How to use this dataset</h1> |
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<ul> |
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<li>Create a model for predicting mortality caused by Heart Failure.</li> |
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<li>Your kernel can be featured here!</li> |
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<li><a aria-label="More datasets (opens in a new tab)" target="_blank" href="https://www.kaggle.com/andrewmvd/datasets">More datasets</a></li> |
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</ul> |
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<h1>Acknowledgements</h1> |
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<p>If you use this dataset in your research, please credit the authors</p> |
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<h3>Citation</h3> |
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<p>Davide Chicco, Giuseppe Jurman: Machine learning can predict survival of patients with heart failure from serum creatinine and ejection fraction alone. BMC Medical Informatics and Decision Making 20, 16 (2020). (<a rel="noreferrer nofollow" aria-label="link (opens in a new tab)" target="_blank" href="https://doi.org/10.1186/s12911-020-1023-5">link</a>)</p> |
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<h3>License</h3> |
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<p>CC BY 4.0</p> |
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<h3>Splash icon</h3> |
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<p>Icon by <a rel="noreferrer nofollow" aria-label="Freepik (opens in a new tab)" target="_blank" href="https://www.flaticon.com/authors/freepik">Freepik</a>, available on <a rel="noreferrer nofollow" aria-label="Flaticon (opens in a new tab)" target="_blank" href="https://www.flaticon.com/free-icon/heart_1186541">Flaticon</a>.</p> |
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<h3>Splash banner</h3> |
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<p>Wallpaper by <a rel="noreferrer nofollow" aria-label="jcomp (opens in a new tab)" target="_blank" href="https://br.freepik.com/jcomp">jcomp</a>, available on <a rel="noreferrer nofollow" aria-label="Freepik (opens in a new tab)" target="_blank" href="https://br.freepik.com/fotos-gratis/simplesmente-design-minimalista-com-estetoscopio-de-equipamento-de-medicina-ou-phonendoscope_5018002.htm#page=1&query=cardiology&position=3">Freepik</a>.</p> |
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</div></div></div> |