SBM4305: Cardiovascular Diseases Case Study - Processing of ECG Test - Nursing Assignment Help

Assignment Task :

Assessment Details:
This quiz will assess your knowledge of key content areas (Week 1, 2 and 3 contents) and to identify further support needs. For successful completion of the quiz, you are required to study the material provided (lecture slides, tutorials, and reading materials), engage in the unit’s activities, and in the discussion forums. The prescribed textbook is the main reference along with the recommended reading material. By completing this assessment successfully, you will be able to identify key aspects of scope management as per best project management practices. This will then help in achieving ULO1, this in turn will help you in achieving CLO-1, which collectively with other unit learning outcomes will help in achieving GA2.

Assessment Details:
Introduction.
Cardiovascular diseases (CVDs) are the number one of death globally: more people die annually from CVDs than from any other cause. Most CVDs can be prevented by addressing behavioural risk factors such as tobacco use, unhealthy diet and obesity, physical inactivity and harmful use of alcohol using population-wide strategies.
People with CVD or who are at high cardiovascular risk (due to the presence of one or more risk factors such as hypertension, diabetes, hyperlipidaemia or already established disease) need early detection and management using counselling and medicines, as appropriate.

Professor John Price is a heart surgeon. He published a number of research paper in the area of CVDs.
Dr Ben Williams as a physicist and a mathematician whose research interests are bio-medical statistics and mathematical models.
John and Ben worked together on a Machine Learning project related to processing of ECG test data for detecting heart diseases. They performed hundreds of electrocardiogram (ECG) tests on patients with CVDs. Analysing ECG tests they came up with a conclusion that some heart diseases with a high probability can be diagnosed using Machine Learning algorithms.

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