Search results
A public health dataset focused on heart disease, available for download and analysis on Kaggle.
Heart Disease EDA & Prediction 7+ Models | Kaggle. Explore and run machine learning code with Kaggle Notebooks | Using data from multiple data sources.
The dataset is publically available on the Kaggle website, and it is from an ongoing ongoing cardiovascular study on residents of the town of Framingham, Massachusetts. The classification goal...
The dataset for this project was sourced from Kaggle, encompassing demographic information (age and sex), and clinical parameters, such as type of chest pain (cp), resting blood pressure (trtbps), serum cholesterol (chol), fasting blood sugar (fbs), and resting electrocardiographic results (restecg).
Jul 1, 2024 · In this video, we will explore how to use Kaggle, a popular platform for data science and machine learning competitions, to analyze heart disease data. Kaggle provides datasets, coding environments, and a community of data scientists to help you enhance your data analysis skills.
The cardiovascular disease dataset is an open-source dataset found on Kaggle. The data consists of 70,000 patient records (34,979 presenting with cardiovascular disease and 35,021 not presenting with cardiovascular disease) and contains 11 features (4 demographic, 4 examination, and 3 social history):
The Heart Failure Prediction dataset is a collection of clinical and demographic features created by combining five heart datasets to predict the likelihood of heart failure. Features. Data Exploration. Obtaining Dataset for Prediction with Machine Learning.
