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This project proposes to develop a dashboard and a tool that utilize machine

learning algorithms to predict stroke risk, aiming to improve stroke awareness,

prevention, and risk management among the general public.

1.3 Objective

The objectives of the project are:

i. To investigate issues in current stroke risk assessing methods and
identify how machine learning can improve it.

ii. To develop a dashboard to visualize data and a tool that employs
Random Forest algorithm to predict stroke risk.

iii. To evaluate the effectiveness of the dashboard and the stroke risk

prediction tool using Technology Acceptance Model (TAM).

1.4 Project Scope

The scopes of the project are:

i. This project employs the random forest algorithm and Python

for stroke risk prediction, using a public Kaggle stroke disease
dataset for training and testing.

ii. Different datasets will be utilized for prediction and dashboard

data visualization, focusing on stroke mortality.

iii. The project will make prediction based on user demographic
details, presence of heart disease and hypertension.

4