The primary goal of this project is to analyze risk factors of stroke and predict whether a patient is likely to suffer a stroke. According to the World Health Organization (WHO) stroke is the 2nd leading cause of death globally, responsible for approximately 11% of total deaths.
In addition, the dataset is used to investigate and predict hypertension, average glucose level and BMI with the purpose to evaluate if features in the dataset are sufficient for accurate predictions.
The dataset consists of 10 metrics for a total of 5110 patients. These metrics include patients’ demographic data (gender, age, marital status, type of work and residence type) and health records (hypertension, heart disease, average glucose level, Body Mass Index (BMI), smoking status and experience of stroke).
EDA and statistical inference part of this project can be found in here.
ML part of this project can be found here.
The Web App part of this project can be found in the app folder.
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