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
扩展型UCI超声心动图数据集（Extended UCI Echocardiogram Dataset）基于原始UCI超声心动图数据集构建，属于合成数据集。该数据集包含100000条样本与17个变量，涵盖心脏病发作后一年内存活或死亡的患者群体。研究人员通过统计技术对数据集进行扩展，在保留原始数据集分布特征完整性的同时，维持了数据的现实变异性。本数据集专为生存分析、预测建模及临床决策相关研究设计。

2. 数据集用途
本数据集可应用于以下场景：
生存分析：预测心脏病发作后的生存概率
特征重要性分析：识别影响生存结局的关键临床预测因子
机器学习模型开发：训练并评估针对生存结局的预测模型
临床研究：探索临床变量与患者结局之间的关联

3. 变量说明
本数据集共包含17个变量，其中16个为特征变量，1个为目标变量。下文为各变量的详细说明：
特征变量
生存状态（Survival）：
类型：浮点型

5. 数据集统计信息
样本量：100000
变量数：17
目标变量分布：
存活组（alive_at_one = 1）：约30.32%
死亡组（alive_at_one = 0）：约69.68%