Symptom Enhanced Disease Detection using CNN and Siamese Neural Network

• Project Focus: Early disease detection through ocular images.
• Key Methodology: CNN for feature extraction, Siamese NN for similarity measurement.
• Target Population: Millions facing visual impairments in India.
• Benefits: Reduces blindness prevalence by detecting diseases at incipient stages.
• Technological Tools: Python, TensorFlow, Flask, HTML, CSS, CNN, Pandas, Matplotlib, Siamese NN.
• Market Strategy: Digital campaigns, collaborations with healthcare professionals.
• Impact: Transformative for individuals' health and well-being.
• Innovation: Advances disease diagnostics through AI-powered tools.
• Future Outlook: Redefines precision medicine with cutting-edge ML integration.

Getting Started

These instructions will help you set up and run the project on your local machine.

Prerequisites

Ensure you have the following installed:

• Python
• Flask
• BeautifulSoup
• Tensorflow
• Spacy
• Pandas

Installation

1. Clone the repository:

   git clone [https://github.com/your-username/your-repository.git](https://github.com/blizet/EyeScan.git)

2. Navigate to the project directory:

   cd your-repository

Running the Application

1. Go to the backend folder:

   cd backend

2. Ensure you have Python installed.

3. Install the required dependencies:

   pip install -r requirements.txt

4. Run the main file app.py using Flask:

   flask run

Application