This repository contains the code for a machine learning model that predicts the likelihood of a patient having a stroke. The model is deployed on the website https://thalma8-stroke-prediction--app-am912r.streamlit.app/ using the streamlit framework and python.
#Requirements The following packages are required to run this project:
pandas==1.5.2 pyngrok==5.1.0 scikit_learn==1.2.1 streamlit==1.15.0 #Usage Clone this repository: git clone https://github.com/thalma8/stroke-prediction Navigate to the project directory: cd stroke-prediction Install the required packages: pip install -r requirements.txt Run the streamlit app: streamlit run app.py Access the app by visiting http://localhost:8501 in your web browser. #Model The stroke prediction model is built using scikit-learn and is based on patient data such as age, gender, blood pressure, and more. The model was trained on a large dataset and has achieved good performance in terms of accuracy.
#Deployment The model is deployed on the website https://thalma8-stroke-prediction--app-am912r.streamlit.app/ using the streamlit framework. This allows users to easily interact with the model and make predictions by inputting their own data.