🧠 Neuro Tech Care (Medalgnosis)

🚀 AI-Powered Brain Tumor Diagnosis with Privacy-First Approach

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📌 Overview

Neuro Tech Care is an intelligent medical application designed to revolutionize brain tumor diagnosis using AI-driven MRI analysis.

The system leverages Microsoft Azure Custom Vision to detect brain tumors such as:

• Meningioma
• Glioma
• Pituitary Tumors

With a strong focus on data privacy, accuracy, and accessibility, the platform ensures that no user data or MRI scans are stored, making it a secure and patient-centric solution.

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🎯 Problem Statement

Traditional brain tumor diagnosis using MRI scans:

• Time-consuming
• Prone to human error
• Lacks strong privacy mechanisms

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💡 Solution

Medalgnosis introduces:

• Fast AI-based MRI analysis
• Accurate tumor detection using Azure AI
• Privacy-first architecture (no data storage)
• Detailed tumor insights & treatment guidance
• Seamless doctor appointment integration

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🌍 Theme

Creating a brighter future for health by leveraging cutting-edge technology and compassionate care.

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✨ Key Features

• AI Tumor Detection
  Detects multiple tumor types using trained ML models

• Detailed Medical Insights
  Provides:

  • Tumor characteristics
  • Causes & symptoms
  • Effects & risks
  • Treatment options

• Personalized Recommendations
  Suggests treatment paths based on tumor type

• Privacy First

  • No data storage
  • No MRI retention
  • Secure processing

• Doctor Appointment Integration
  Powered by Azure Logic Apps

• User-Friendly Interface
  Built using Streamlit for easy interaction

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🛠️ Tech Stack

• Python
• Streamlit
• Streamlit Community Cloud
• Microsoft Azure Custom Vision
• Azure Logic Apps
• GitHub

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🧑‍💻 Developer

Aaqeeb Pinjari

• Location: Aurangabad, India
• Graduation Year: 2024

💼 Role & Contribution

• Worked on Azure backend integration
• Implemented Azure Custom Vision model pipeline
• Integrated AI model with Streamlit frontend
• Connected Azure Logic Apps for appointment workflow

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⚙️ Installation Guide

🔹 Prerequisites

• Python (3.x)
• Azure Account

👉 Get Azure: https://azure.microsoft.com/en-in/free

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🔹 Setup Steps

1. Clone the repository:

git clone <your-repo-link>
cd <project-folder>

2. Install dependencies:

pip install -r requirements.txt

3. Configure Azure: Create Azure Custom Vision resource Train model Get Endpoint & Key Configure Logic App: Create Logic App with HTTP Trigger Add Send Email (V2) action

4. Edit predictor.py: Replace Azure Endpoint Replace API Key Replace Logic App URL

5. ▶️ Run Application

streamlit run about.py

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⭐ Support If you like this project:

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