Title: VitalVision Cardiac Risk Detection
Description: A healthcare monitoring application that uses machine learning and computer vision to capture and analyze patient vitals from ICU monitor images, aiding healthcare providers in making informed decisions for patient care.
Project Setup Prerequisites Python 3.7 or higher Flask web framework OpenCV TensorFlow OCR (Optical Character Recognition) library LangChain.js Installation Clone the repository: bash Copy code git clone https://github.com/yourusername/vitalvision-cardiac-risk-detection.git Change directory to the project folder: bash Copy code cd vitalvision-cardiac-risk-detection Create a virtual environment: Copy code python -m venv venv Activate the virtual environment: On Windows: Copy code venv\Scripts\activate On macOS/Linux: bash Copy code source venv/bin/activate Install the required dependencies: Copy code pip install -r requirements.txt Running the Flask app Set the environment variable: On Windows: arduino Copy code set FLASK_APP=app.py On macOS/Linux: arduino Copy code export FLASK_APP=app.py Run the Flask app: arduino Copy code flask run Open a web browser and navigate to http://127.0.0.1:5000/ to access the application.