Heart Disease Diagnosis
Dataset
The classic Cleveland heart disease dataset from the UCI Machine Learning Repository, containing 297 patient samples and 13 clinical examination indicators, widely used for binary classification prediction and medical data analysis research.
Dataset Highlights
Classic medical dataset, suitable for clinical data analysis from beginner to advanced levels
Real Clinical Data
The data comes from real patient records at the Cleveland Clinic, including 13 clinical indicators such as age, gender, type of chest pain, blood pressure, cholesterol, etc.
Classic Binary Classification Task
Predict whether a patient has heart disease, making it an ideal dataset for learning classification algorithms like logistic regression, SVM, and random forests.
Introduction to Medical AI
One of the most commonly used medical datasets, helping to understand how to apply machine learning to clinical decision support systems.
Diversity of Features
Includes continuous (blood pressure, cholesterol) and categorical (type of chest pain, ECG results) features, suitable for data preprocessing practice.
Academic Literature Support
The dataset has been collected by multiple cardiology experts and is widely cited in academic journals such as the International Journal of Machine Learning.
UCI Authoritative Source
Originating from the UCI Machine Learning Repository, it has been the standard benchmark dataset in the field of heart disease prediction for nearly 40 years.
Applicable Scenarios
From classroom teaching to medical research, it can provide value
Clinical Decision Support
Build heart disease risk prediction models to assist doctors in preliminary screening and diagnostic reference
Binary Classification Modeling
Use algorithms such as logistic regression, SVM, and random forests for heart disease prediction
Feature Importance
Analyze which clinical indicators are most predictive of heart disease diagnosis
Data Visualization
Explore the distribution and correlation of various indicators, suitable for medical data EDA practice
Data Preview
The following are examples of the first few rows of the Cleveland heart disease dataset
age,sex,cp,trestbps,chol,fbs,restecg,thalach,exang,oldpeak,slope,ca,thal,target 63.0,1.0,1.0,145.0,233.0,1.0,2.0,150.0,0.0,2.3,3.0,0.0,6.0,0 67.0,1.0,4.0,160.0,286.0,0.0,2.0,108.0,1.0,1.5,2.0,3.0,3.0,2 67.0,1.0,4.0,120.0,229.0,0.0,2.0,129.0,1.0,2.6,2.0,2.0,7.0,1 37.0,1.0,3.0,130.0,250.0,0.0,0.0,187.0,0.0,3.5,3.0,0.0,3.0,0 41.0,0.0,2.0,130.0,204.0,0.0,2.0,172.0,0.0,1.4,1.0,0.0,3.0,0
3 Steps to Get Started Quickly
From browsing to analysis, you can start your data science project in minutes
Browse the Dataset
View dataset details on the Ace Data Cloud platform, understand field descriptions, sample size, and licensing agreements, and other metadata.
Download Data
Download the CSV file (18 KB), data is ready to use, no additional cleaning required.
Load and Analyze
Use pandas.read_csv() to load the data, and start exploratory analysis, modeling, and visualization.
Start Exploring Heart Disease Diagnosis Data
A classic medical dataset, open license, available for immediate download. Whether you are a beginner in medical AI or an experienced data scientist, this dataset is worth trying.