{
  "fetched_at": "2026-10-20T07:20:35Z",
  "source_url": "https://www.kaggle.com/competitions/gusto-1/data",
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      "name": "rules",
      "content": "\r\n\t<!-- Begin Base Rules -->\r\n    <h3>One account per participant</h3>\r\n    <p>You cannot sign up to Kaggle from multiple accounts and therefore you cannot submit from multiple accounts.</p>\r\n    <h3>No private sharing outside teams</h3>\r\n    <p>\r\n        Privately sharing code or data outside of teams is not permitted.\r\n        It's okay to share code if made available to all participants on the forums.\r\n    </p>\r\n    <h3>Team Mergers</h3>\r\n    <p>Team mergers are not allowed in this competition.</p>\r\n\r\n    <h3>Team Limits</h3>\r\n    <p>There is no maximum team size.</p>\r\n    <h3>Submission Limits</h3>\r\n    <p>You may submit a maximum of 2 entries per day.</p>\r\n    <p>You may select up to 2 final submissions for judging.</p>\r\n    <h3>Competition Timeline</h3>\r\n    <p>Start Date: <strong>TBA</strong></p>\r\n    <p>Merger Deadline: <strong>None</strong></p>\r\n    <p>Entry Deadline: <strong>None</strong></p>\r\n    <p>End Date: <strong>2/1/2014 12:00 AM UTC</strong></p>\r\n\t<!-- End Base Rules -->\r\n<p>The rules page is a bit special: it will auto-update the text based on the parameters of the competition. The rules you need to add here are any additional rules relating to dataset usage. You may also put grading information here.</p>",
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      "content": "<h2>File descriptions</h2>\n<ul>\n<li><strong>train.csv</strong> - the training set</li>\n<li><strong>test.csv</strong> - the test set</li>\n<li><strong>sampleSubmission.csv</strong> - a sample submission file in the correct format</li>\n</ul>\n<h2>Data fields</h2>\n<ul>\n<li><strong>DAY30</strong> - The 30 Day mortality</li>\n<li><strong>AGE</strong> - Age in years</li>\n<li><strong>A65</strong> - Age &gt;65 years (0/1)</li>\n<li><strong>SEX</strong> Gender (male=0, female=1)</li>\n<li><strong>KILLIP</strong> Killip class (1–4): A measure for left ventricular function</li>\n<li><strong>SHO</strong> Shock: Killip class 3/4 vs. 1/2 (0/1)</li>\n<li><strong>DIA</strong> Diabetes (0/1)</li>\n<li><strong>HYP</strong> Hypotension: Systolic BP&lt;100 (0/1)</li>\n<li><strong>HRT</strong> Heart rate: Pulse&gt;80 (“tachycardia,” 0/1)</li>\n<li><strong>ANT</strong> Anterior infarct location (0/1)</li>\n<li><strong>PMI</strong> Previous myocardial infarction (0/1)</li>\n<li><strong>HIG</strong> High risk: ANT or PMI (0/1)</li>\n<li><strong>HEI</strong> Height in cm</li>\n<li><strong>WEI</strong> Weight in kg</li>\n<li><strong>SMK</strong> Smoking (1 = never; 2 = exsmoker; 3 = current smoker)</li>\n<li><strong>HTN</strong> Hypertension history (0/1)</li>\n<li><strong>LIP</strong> Lipids: Hypercholesterolaemia (0/1)</li>\n<li><strong>PAN</strong> Previous angina pectoris (0/1)</li>\n<li><strong>FAM</strong> Family history of MI (0/1)</li>\n<li><strong>STE</strong> ST elevation on ECG: Number of leads</li>\n<li><strong>ST4</strong> ST elevation on ECG: &gt;4 leads (0/1)</li>\n<li><strong>TTR</strong> Time to relief of chest pain &gt; 1 h (0/1)</li>\n</ul>",
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      "name": "Description",
      "content": "<p>The goal of this competition is to predict 30 day mortality in patients who have suffered from an acute myocardial infarction. The data set consists of a subset of the GUSTO-I trial data.</p>\n<p>This data set is used an example data set in the book of E.W. Steyerberg - <em>Clinical Prediction Models.</em> A description is provided on page 411:</p>\n<blockquote>\n<p>Acute myocardial infarction (heart attack) is caused by the formation of a clot in one of the coronary arteries that supply blood to the heart muscle. Acute MI is a major public health problem. The age-adjusted incidence of hospitalization for<br />myocardial infarction is around 2 per 1,000 women and 4 per 1,000 for men in the United States. 350 Mortality is substantial in the period immediately after the event, and also during the years after surviving the initial infarction. Some patients die before reaching hospital. Patients seen in hospitals are reported to have an average mortality within 30 days around 6–15%.<br />The risk of 30-day mortality strongly depends on various prognostic factors (Table 22.1 ). In younger patients, risks are much lower than in older patients. Other patient demographics are also important (gender, length, weight), as well as the presence of risk factors (hypertension, diabetes, smoking, family history) and the history of previous cardiovascular events (previous MI, angina, stroke, bypass surgery). Relevant presenting characteristics include the location of the infarction and the extent of ECG abnormalities. Very important is the acute state of the patient as reflected by blood pressure, heart rate, and left ventricular function (Killip class, presence of shock).</p>\n</blockquote>",
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      "name": "Evaluation",
      "content": "<p>Submissions will be scored by the AUC</p>\n<h2>Submission Format</h2>\n<p>Submission files should contain two columns: Id and Prediction. ID is the row number of the test set and Prediction is the predicted probability.</p>\n<pre>Id,Prediction<br /><span style=\"font-size: 14px; line-height: 1.4em;\">1,0.0584192440070097<br />2,0.0886699507389171<br />3,0.0584192440070097<br /></span><span style=\"font-size: 14px; line-height: 1.4em;\">etc.</span></pre>",
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