krishgaur1354 / medisync

Our platform empowers users to upload their medical imaging patterns, including MRIs and X-Ray scans

MediSync

Project Overview

MediSync is a groundbreaking website dedicated to diagnostics and the early detection of respiratory diseases, such as Emphysema or Bronchitis. Our platform empowers users to upload their medical imaging patterns, including MRIs and X-Ray scans. Leveraging advanced Machine Learning algorithms trained specifically for respiratory disease detection, we provide users with predictive insights into the likelihood of having contracted these diseases.

Features

• Upload Medical Images: Users can easily upload their MRIs and X-Ray scans through our user-friendly interface.

• Respiratory Disease Prediction: Our state-of-the-art Machine Learning algorithm analyzes the uploaded medical images to predict the probability of early onset respiratory diseases.

• Secure and Confidential: We prioritize the security and confidentiality of user data. All medical information is handled with the utmost care and compliance with privacy standards.

How it Works

1. User Registration: Create an account on MediSync to access the full range of features.

2. Upload Medical Images: Use the intuitive interface to upload your MRIs and X-Ray scans securely.

3. Algorithm Analysis: Our specialized Machine Learning algorithm processes the medical images to provide predictive insights.

4. View Results: Users can view detailed results and probabilities related to the likelihood of specific respiratory diseases.

Getting Started

To get started with MediSync, follow these steps:

1. Clone the repository:

   git clone https://github.com/your-username/medisync.git

2. Navigate to the project directory:

   cd medisync

3. Install dependencies:

   npm install

4. Run the application:

   npm start

Technologies Used

• Frontend: HTML, CSS, JavaScript
• Backend: Node.js, Express
• Machine Learning: TensorFlow, sci-kit-learn

Contributing

We welcome contributions from the community. If you have ideas for improvements or want to report issues, please submit a GitHub issue or create a pull request.

License

This project is licensed under the MIT License.