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Stroke Classification using Machine Learning

Kuan, Rachel Khye Xin (2019) Stroke Classification using Machine Learning. IRC, Universiti Teknologi PETRONAS. (Submitted)

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Stroke is at the second place of leading cause of mortality in worldwide and it has been a concern to an individual and also to the national healthcare system. Stroke risk factors include heart attack/ cardiac disease, diabetes, hypertension, lifestyle and more factors. This paper presents “Stroke Classification Using Machine Learning” to classify the stroke of the person upon assessing the risk factors from the health report. Early diagnosis of stroke is essential for prevention and treatment. It is the most important reason of death, which is due to clot and break in the blood vessels and cause the tissue inside the brain to be damage. It is one of the leading causes of adult disability today as the recovery rate for stroke patient is a very slow process which and very the treatment is very expensive. Prevention is better than cure, a solution to reduce recovery time duration and prevent disease. A prototype was developed using Rapid Application Development. The project was designed to provides a better way for classify stroke.

Item Type: Final Year Project
Academic Subject : Academic Department - Information Communication Technology
Subject: Q Science > Q Science (General)
Divisions: Sciences and Information Technology > Computer and Information Sciences
Depositing User: Ahmad Suhairi Mohamed Lazim
Date Deposited: 10 Sep 2021 08:58
Last Modified: 10 Sep 2021 08:58
URI: http://utpedia.utp.edu.my/id/eprint/20952

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