ErSangram / Capstone_03_Cardiovascular_Risk_Prediction

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Capstone_04_Cardiovascular_Risk_Prediction

Project Summary -

Before diving into the project, lets discuss what are Cardiovascular diseases and some of their major causes.
Cardiovascular diseases, also called CVDs, are the leading cause of death globally, causing an estimated 17.9 million deaths each year.
CVDs are a group of disorders of the heart and blood vessels and include coronary heart disease, cerebrovascular disease, rheumatic heart disease and other conditions. More than four out of five CVD deaths are due to heart attacks and strokes, and one third of these deaths occur prematurely in people under 70 years of age.
The most important behavioural risk factors of heart disease and stroke are unhealthy diet, physical inactivity, tobacco use and harmful use of alcohol. The effects of behavioural risk factors may show up in individuals as raised blood pressure, raised blood glucose, raised blood lipids, and overweight and obesity.

Screenshot 2023-10-19 163122

Problem Statement -

Cardiovascular diseases (CVDs) are the leading cause of death globally, taking an estimated 17.9 million people died from CVDs in 2019, representing 32% of all global deaths. Of these deaths, 85% were due to heart attack and stroke.
More than four out of five CVD deaths are due to heart attacks and strokes, and one third of these deaths occur prematurely in people under 70 years of age. The most important behavioural risk factors of heart disease and stroke are unhealthy diet, physical inactivity, tobacco use and harmful use of alcohol. Over three quarters of CVD deaths take place in low- and middle-income countries.
Objective -The classification goal is to predict whether the patient has a 10-year risk of future coronary heart disease (CHD) based on their health statistics and information about their tobacco usage.

Business Objective:-

The primary objective of this project is to leverage machine learning and predictive analytics to assess and classify patients' 10-year risk of developing coronary heart disease (CHD) based on their health metrics and tobacco usage information. This predictive model will aid healthcare professionals in proactively identifying individuals at a higher risk of CHD, allowing for early intervention, personalized medical advice, and lifestyle recommendations to reduce the prevalence of heart disease. By achieving this objective, we aim to improve the overall health and well-being of individuals, reduce healthcare costs, and contribute to better health outcomes in the population.

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