Stroke prediction using machine learning is a hot topic in medical field and scientific research. Using machine learning algorithms to analyze medical data can reveal hidden connections between various factors and the risk of stroke. This helps doctors and public health professionals identify people at increased risk of stroke and take appropriate preventative measures. This approach leads to more accurate and personalized medical care, and can also reduce the incidence of stroke and related complications. In this work, we apply ML methods to predict stroke based on a database consisting of various parameters (age, gender, weight, etc.) that affect a person's risk of stroke. Our telegram bot allows you to quickly and conveniently assess whether a person may be susceptible to developing a stroke or not. However, it is always important to seek medical advice.
- data/* - dataset files used
- models/*- files used building, learning and testing ML module
- notebooks/*- preprocessing, visualization of data
- data preprocessing
- data visualization
- prediction_model