Stroke Predictor

https://github.com/aaditya9803/Stroke-Predictor

https://github.com/aaditya9803/Stroke-Predictor/-/wikis/home

Project Description

Stroke Predictor is a web app that helps users predict their risk of having a stroke. Users can learn about strokes through visualizations. Developers can explore how the data was processed and trained for Stroke Predictor.

Installation

Versions:

• Python 3.10.16
• streamlit 1.41.1
• rasa 3.6.20

How to start

Start rasa actions: rasa run actions -p 8080

Start rasa server: rasa run --enable-api -p 8000

Start the web app service: streamlit run main.py

Open the app in the browser with URL: http://localhost:8501

Data

The Stroke Prediction Dataset was accessed from following source:

https://www.kaggle.com/datasets/fedesoriano/stroke-prediction-dataset

Further details about the data are also described in the Wiki.

Basic Usage

After downloading the project files in a project folder, do the following steps:

1. Download Anaconda Navigator https://www.anaconda.com/download/success
2. Launch Anaconda Prompt
3. Create Conda Environment conda create --name stroke-predictor python==3.10.16
4. Activate Conda Environment conda activate stroke-predictor
5. Go to the Project folder cd project-folder
6. Install all the required packages in requirements.txt pip install -r requirements.txt
7. Train the Rasa model rasa train
8. Start Rasa action server rasa run actions -p 8080
9. Start Rasa server rasa run --enable-api -p 8000
10. Start Streamlit Server streamlit run main.py

Then call the streamlit URL 'localhost:8051', in the browser.

Work done

All work by Aaditya Neupane.