🧠 Medi-Sense

A unified health diagnostic platform that integrates four powerful machine learning models—Detect Sepsis, Diabetes, Stress, and Brain Tumor—all in one place. Medi-Sense aims to assist users in understanding potential health risks through AI-driven predictions.

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🗂️ Project Structure

medi-sense/

  ├── client/
  ├── server/
  ├── server_python/
  └── README.md

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🚀 Features

• ✅ Brain Tumor Detection via MRI Images (CNN)
• ✅ Stress Level Detection using Mental Health Questionnaire
• ✅ Diabetes Risk Prediction using Health Data
• ✅ Sepsis Prediction using Clinical Measurements
• 🧩 Easy-to-use unified interface
• 🌐 Fully responsive web application
• 🔗 Node.js + Flask hybrid backend

🛠️ Tech Stack

Frontend (📁 client)

• React.js
• Tailwind CSS
• Axios for API calls

Backend (📁 server)

• Node.js
• Express.js
• JWT Auth (if implemented)
• MongoDB

ML Model APIs (📁 server_python)

• Python 3.x
• Flask
• Scikit-learn / TensorFlow
• Trained models serialized with joblib or pickle

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📦 Installation

git clone https://github.com/yourusername/medi-sense.git

cd medi-sense

📦Install client dependencies

cd client
npm install

📦Install Server dependencies

cd client
npm install

📦Setup server_python

Create /PKL folder in server_python

Download models from below link and place them in /PKL/ folder https://drive.google.com/drive/folders/1TDX3nRaRHqU9FS4byL-J79DBQxgwv_US?usp=drive_link

> pip install requirement.txt

Execute client, server and python_server

client

> cd client
> npm run dev

server

> cd server
> npm test

server_python

> cd server_python
> python app.py

📸 Screenshots

🏠 Login/Signup Page

🔐 Dashboard

🏠 Models

Made with ❣️ by

Harsh
Jay
Krish
Nisheet