Realm.ai was an interdisciplinary project for the MSc Health, and Digital Transformation cohort 2023/2024. Group members included: Johann, Daniel, Fré, Evita and Suleyman. This project was designed to enhance transparency in AI software development for healthcare. We created a prototype/concept version of a system which aims to enable clear monitoring and certification of machine learning models to improve trust and adoption in the healthcare sector. It utilizes blockchain technology to create a decentralized process, allowing users to submit, validate, and revalidate machine learning models securely and transparently.

• Model Submission: Users can submit their machine learning models along with associated metadata.
• Model Validation: Submitted models are validated against predefined criteria to ensure they meet minimum standards.
• Revalidation: Models can be revalidated to update their performance metrics and compliance status.
• Model Results Retrieval: Users can retrieve detailed results and status of any submitted model by its unique identifier.
• Decentralized Storage: All transactions are recorded on a blockchain, ensuring data integrity and transparency.

• Ethereum Blockchain: For creating a transparent and immutable record of model validations.
• Smart Contracts: Used to enforce validation rules and record model information.
• Node.js: Server-side logic including API endpoints for interacting with the blockchain.
• Express.js: Framework for handling HTTP requests and serving the API.
• Ethers.js: Library for interacting with the Ethereum blockchain and smart contracts.
• HTML/CSS/JavaScript: For the frontend to interact with the smart contracts through a web interface.

• Node.js and npm
• Git### Cloning the Repository

git clone https://github.com/your-username/realm.ai.git
cd realm.ai

npm install

Create a .env file in the project root and add the following variables:

RPC_URL="Your_Ethereum_Node_URL"
PRIVATE_KEY="Your_Wallet_Private_Key"
CONTRACT_ADDRESS="Deployed_Contract_Address"

node server.js or npm start

The server will start running on http:https://localhost:3000. Visit the localhost to interact with the API, you can now upload model information, submit them for validation, update them, and get results.

Contributions are welcome. Please feel free to submit pull requests, create issues, or suggest improvements.

MIT