Echocardiogram dataset for survival analysis

Dataset Documentation: Extended UCI Echocardiogram Dataset 1. Overview The Extended UCI Echocardiogram Dataset is a synthetic dataset based on the original UCI Echocardiogram dataset. It comprises 100,000 samples and 17 variables, representing patients who either survived or died within one year after a heart attack. The dataset was expanded using statistical techniques to maintain realistic variability while preserving the integrity of the original dataset's patterns. It is designed for survival analysis, predictive modelling, and clinical decision-making research. 2. Dataset Purpose The dataset is intended for: Survival Analysis: Predicting the likelihood of survival post-heart attack. Feature Importance Analysis: Identifying key clinical predictors of survival. Machine Learning Model Development: Training and evaluating predictive models for survival outcomes. Clinical Research: Exploring relationships between clinical variables and patient outcomes. 3. Variables The dataset contains 17 variables, including 16 features and one target variable. Below is a detailed description of each variable: Features Survival: Type: Float 5. Dataset Statistics Number of Rows: 100,000 Number of Columns: 17 Target Variable Distribution: Survived (alive_at_one = 1): ~30.32% Deceased (alive_at_one = 0): ~69.68%数据集文档：扩展型UCI超声心动图数据集（Extended UCI Echocardiogram Dataset） 1. 概述 本扩展型UCI超声心动图数据集是基于原始UCI超声心动图数据集构建的合成数据集，共包含100000条样本与17项变量，覆盖心梗后一年内存活或死亡的患者群体。该数据集通过统计技术完成扩展，在保留原始数据集模式完整性的同时，维持了真实的变量分布变异性，专为生存分析、预测建模与临床决策研究设计。 2. 数据集用途 本数据集应用场景如下： - 生存分析：预测心梗后患者的生存概率 - 特征重要性分析：识别影响患者生存的关键临床预测因子 - 机器学习模型开发：训练并评估用于生存结局预测的预测模型 - 临床研究：探索临床变量与患者转归之间的关联 3. 变量说明 本数据集共包含17项变量，其中16项为特征变量，1项为目标变量。下文将对各项变量进行详细说明： 特征变量 生存时长（Survival）： 类型：浮点型 5. 数据集统计信息 样本行数：100000 变量列数：17 目标变量分布： 存活（alive_at_one = 1）：约30.32% 死亡（alive_at_one = 0）：约69.68%