心血管疾病数据集

用于分析心血管疾病风险因素并构建预测模型的表格数据集。

Jen-uisJen-uis
GitHub
2024-05-23 更新
浏览 41
表格心血管疾病预测模型
Cardiovascular Disease Dataset

基本信息

模态
表格
大小
0.00102 GB
许可
MIT
创建/更新时间
2024-05-23
版本
main

资源简介

心血管疾病数据集

【数据集背景】

本数据集源站标题为《Jen-uis/Cardiovascular-Disease-Dataset》。源站首次发布:2024-05-23。

【数据内容】

源站原始描述:This repository contains project materials for the Winter STAT 232 class, University of California, Riverside, A. Gary Anderson School of Management. # Cardiovascular-Disease-Dataset This repository contains project materials for the Winter STAT 232 class, University of California, Riverside, A. Gary Anderson School of Management. ## Introduction For those who are new to this folder, the `Project-Code.Rmd`, `Project-Code.html`, and `Project-Code.Rproj` files are our main coding files. This proje…

【适用方向】

结构化表格数据可直接用于统计建模、特征工程与队列分析。

【获取与许可】

源站页面:https://github.com/Jen-uis/Cardiovascular-Disease-Dataset

使用许可:MIT。

官方服务

专家保障全链路合规授权与标注交付

陕川双基地 × 超十家三甲医院直连

从合规授权、采集治理、专业标注到数据集交付,我们提供全链路闭环服务,让高质量临床数据即拿即用。

⚡️ 需要原始数据或标注支持?联系我们获取定制方案。

帮我联系

下载信息

注册下载

需要注册 Kaggle 账号并登录后下载,适合需要跟踪下载记录和使用 API 的用户。

暂未开放

公开下载

无需注册即可直接获取公开样本或文档,适合快速预览和评估数据集质量。

免登录

有偿下载

公开数据集受托下载与技术交付服务。

提供高速下载与技术交付服务(收技术服务费,非数据销售)

暂未开放

当前数据集主要来源为 Kaggle 公开托管,完整影像包建议通过原始链接或 Kaggle API 获取。

使用方式

数据集获取

git clone https://github.com/Jen-uis/Cardiovascular-Disease-Dataset.git

curl -L -o repo.zip https://github.com/Jen-uis/Cardiovascular-Disease-Dataset/archive/refs/heads/main.zip
unzip repo.zip

源站 README 摘录(使用方式)

Cardiovascular-Disease-Dataset

This repository contains project materials for the Winter STAT 232 class, University of California, Riverside, A. Gary Anderson School of Management.

Introduction

For those who are new to this folder, the Project-Code.Rmd, Project-Code.html, and Project-Code.Rproj files are our main coding files. This project is completed using R Markdown in R Studio. The data is originally obtained from Kaggle.com, link will be attached below. Feel free to explore more options beyond this analysis report.

Project Idea

This project focuses on analyzing a cardiovascular disease dataset to develop predictive models that can identify individuals at risk of developing cardiovascular diseases. Using various data analysis and machine learning techniques, we aim to uncover significant patterns and risk factors associated with cardiovascular conditions. The project involves data preprocessing, exploratory data analysis, feature selection, and model training and evaluation. The ultimate goal is to create a reliable prediction model that can aid healthcare providers in early detection and prevention of cardiovascular diseases, ultimately contributing to better patient outcomes and public health strategies.

Contents

  • Project-Code.Rmd: This contains the R Markdown code which contains most of our analysis coding.
  • Project-Code.html: HTML export of the R Markdown file for easy reading.
  • Final-Report.docs: Documents which reports our finding and analysis during the project.
  • Data Folder: Contains the datasets used for analysis. This dataset is uploaded by Svetlana Ulianova. Disclaimer: The data is obtained from Kaggle.com Cardiovascular Disease Dataset. All data are used for educational purposes only. Do not republish Ulianova’'s work without approval. License: Data files are copyrighted by the original authors

License

This project is licensed under the MIT License. See the LICENSE file for more details.

Contributing

This project had been finished at March 2024, no changes shall be made to this main repository. No edits will be approved.

Contact

If you have any questions or need further information, please contact our team at: connectnathaniel@gmail.com
Authors:

  • Nathaniel Zhu
  • Ankit Malhotra
  • Hong Che

数据加载示例(表格/文本类)

import pandas as pd, glob, os

files = (glob.glob(os.path.join(path, "**", "*.csv"), recursive=True)
       + glob.glob(os.path.join(path, "**", "*.tsv"), recursive=True)
       + glob.glob(os.path.join(path, "**", "*.xlsx"), recursive=True))
print("数据文件:", files)
df = pd.read_csv(files[0])
print(df.shape); print(df.columns.tolist()); print(df.head(3))

完整仓库:github.com/Jen-uis/Cardiovascular-Disease-Dataset

数据缺失?

依托陕西、四川两大基地,我们与超过十家三甲医院建立直接合作关系,覆盖合规授权、采集治理、专业标注、数据交付的全流程,为AI医疗团队提供即拿即用的高质量临床数据。

⚡️ 需要数据支持或标注服务?立即联系我们获取专业方案。

获取专属数据定制方案