By unraveling the risk profile of heart disease, this research aims to equip healthcare practitioners with personalized assessment tools to curb the incidence and burden of cardiovascular mortality. This heart disease dataset is curated by combining 3 popular heart disease datasets The first dataset (collected from kaggle) contains 70000 records with 11 independent features which makes it the largest heart disease dataset available so far for research purposes. 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. For this study, i am performing an exploratory data analysis on a kaggle dataset on cardiovascular diseases with the aim of discovering meaningful insights and hopefully, in the nearest.
This dataset contains information related to patients with heart disease and is highly useful for analyzing and predicting the risk of developing heart conditions. Our dataset has standard health information and information on the presence/absence of cardiovascular disease for over 70,000 patients. Personal key indicators of heart disease by cdc | cogito, ergo sum Health dataset on kaggle, the personal key indicators of heart disease, 2020 annual cdc survey data of 400k adults related to their health status The dataset can be download from the official site or here. In this dataset, 5 heart datasets are combined over 11 common features which makes it the largest heart disease dataset available so far for research purposes
This project uses data science and machine learning techniques to predict the probability of a patient having heart disease or a heart attack
OPEN
