{
  "fetched_at": "2026-10-25T01:48:26Z",
  "source_url": "https://www.kaggle.com/competitions/coepdsaiinductions/data",
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    {
      "name": "Description",
      "content": "Heart Failure Prediction\n---\n\nCardiovascular diseases (CVDs) are the number 1 cause of death globally, taking an estimated 17.9 million lives each year. People with cardiovascular disease or who are at high cardiovascular risk need early detection and management wherein a machine learning model can be of great help. \n\nUsing the given dataset, develop a model that can predict whether a person is at risk of heart disease. For each patient in the test set, you must predict a 0 (negative) or 1 (positive) for the target variable.",
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      "name": "Evaluation",
      "content": "Metric\nYour score is the percentage of patients you correctly predict. This is known simply as \"accuracy”.\n\nSubmission File Format\nYou should submit a CSV file with exactly 218 entries plus a header row\n(as per the \"heart\\_failure\\_test.csv\" which will be used for your final submission). \nYour submission will show an error if you have extra columns (beyond Id and Prediction) or rows.\n\nThe file should have exactly 2 columns:\n\nId, Prediction (contains your binary predictions: 1 for positive of having a heart attack, 0 for negative)\n\nId,HeartDisease\n\n1,0\n\n2,1\n\n3,0\n\nEtc.\n\nYou can download an example submission file (\"sample_submission.csv\") on the Data page.",
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    {
      "name": "rules",
      "content": " - Apply yourself!\n - Have fun!\n - Don't cheat!, mention all sources of information/copied code, however highly plagiarized code will be a basis for \n   disqualification. ",
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