CardioVision

CardioVision is a medical screening web application with a Flask backend and a static HTML/CSS/JavaScript frontend. It includes symptom scoring, cardiac risk calculation, ECG/X-ray prediction modules, AI chat support, and medical image preprocessing utilities.

Note: This project is for learning and prototype use. It is not a replacement for professional medical diagnosis.

Project Structure

BIO-PROJECT/
|-- backend/
|   |-- App.py
|   |-- ai_chat.py
|   |-- predict_ecg.py
|   |-- predict_xray.py
|   |-- risk_engine.py
|   |-- symptom_scorer.py
|   `-- requirements.txt
|-- frontend/
|   |-- index.html
|   |-- diagnosis.html
|   |-- results.html
|   |-- script.js
|   `-- style.css
|-- preprocessing/
|   |-- __init__.py
|   `-- preprocess.py
|-- models/
|-- data/
`-- README.md

Features

• Flask API backend
• Static frontend served by Flask
• Symptom-based scoring
• Cardiac risk calculation
• ECG and X-ray prediction modules
• Medical image preprocessing with OpenCV
• .env support for local configuration

Requirements

• Python 3.10+
• Anaconda Prompt or PowerShell
• pip

Clone The Project

git clone <your-repository-url>
cd BIO-PROJECT

If you are starting from an empty cloned repository and adding this project:

git add .
git commit -m "Initial CardioVision project"
git branch -M main
git push -u origin main

Setup With Anaconda Prompt

Open Anaconda Prompt inside the project folder:

cd D:\BIO-PROJECT

Create and activate an environment:

conda create -n cardiovision python=3.10 -y
conda activate cardiovision

Install dependencies:

pip install -r backend/requirements.txt

If OpenCV is not available, install it manually:

pip install opencv-python

Environment Variables

Create a .env file in the project root for local secrets/configuration.

Example:

PORT=5000
FLASK_DEBUG=true

Do not upload .env to GitHub.

Test Preprocessing Import

Run this command from the project root:

python -c "from preprocessing.preprocess import apply_medical_preprocessing; print('Preprocessing import works!')"

Run The App

From the project root:

python backend/App.py

Then open:

http://localhost:5000

If you are using the included virtual environment on Windows:

.\venv\Scripts\python.exe backend\App.py

Useful Commands

Install packages:

pip install -r backend/requirements.txt

Run backend:

python backend/App.py

Check preprocessing:

python -c "from preprocessing.preprocess import apply_medical_preprocessing; print('Preprocessing import works!')"

Check git status:

git status

Add and commit changes:

git add .
git commit -m "Update project files"

Push to GitHub:

git push

Notes

• Keep .env, virtual environments, temporary files, datasets, and trained model files out of GitHub unless you intentionally want to publish them.
• Store large datasets and trained weights externally, then document download instructions.
• Use opencv-python for local Anaconda development. Use opencv-python-headless for server deployments when GUI support is not needed.