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OncoAI Survival Prediction API

Overview

The OncoAI Survival Prediction API is a web service designed to predict patient survival rates in oncology using machine learning models. This API provides endpoints for user authentication, survival prediction, and health checks.

Features

  • User Authentication: Secure user registration and login using JWT tokens.
  • Survival Prediction: Predict patient survival rates based on input features.
  • Health Checks: Verify the status of the API, database connection, and model loading.

Project Structure

The project is structured as follows:

  • app/: Contains the main application code.
    • main.py: The entry point of the application.
    • api/: Contains the API endpoints.
      • auth.py: Authentication-related API endpoints.
      • survival.py: Survival analysis-related API endpoints.
    • core/: Contains core application logic.
      • config.py: Configuration settings.
      • model.py: Data models.
      • security.py: Security-related functions.
      • utils.py: Utility functions.
      • models/: Contains additional data models.
    • db/: Contains database-related code.
      • crud.py: CRUD operations.
      • models.py: Database models.
      • session.py: Database session management.
    • schemas/: Contains Pydantic schemas.
      • auth.py: Authentication-related schemas.
      • survival.py: Survival analysis-related schemas.
  • entorno/: Contains environment-related files.
  • static/: Contains static files.
    • neon-app.js: JavaScript file for the Neon app.
    • neon-dark.css: CSS file for the Neon app.
    • oncoai-dashboard.html: HTML file for the OncoAI dashboard.
  • test.db: SQLite database file.

Dependencies

The application uses the following dependencies:

  • FastAPI: A modern, fast (high-performance), web framework for building APIs with Python 3.6+ based on standard Python type hints.
  • SQLAlchemy: The Python SQL toolkit and Object Relational Mapper that gives application developers the full power and flexibility of SQL.
  • Pydantic: Data validation and settings management using Python type annotations.
  • Uvicorn: An ASGI server for serving FastAPI applications.
  • Passlib: Password hashing library for Python.
  • PyJWT: JSON Web Token implementation in Python.
  • Python-dotenv: Reads key-value pairs from a .env file and sets them as environment variables.

Setup

To set up the application, follow these steps:

  1. Create a virtual environment and activate it.
  2. Install the dependencies using pip install -r requirements.txt.
  3. Create a .env file with the necessary environment variables.
  4. Run the application using uvicorn app.main:app --reload.

Testing

To run the tests, use the following command:

pytest

API Endpoints

Authentication

  • POST /auth/register: Register a new user.
  • POST /auth/login: Log in an existing user.
  • POST /token: Obtain an access token for authentication.

Survival Prediction

  • POST /api/predict: Predict patient survival rates based on input features.

Health Check

  • GET /health: Verify the status of the API, database connection, and model loading.

Contributing

Contributions are welcome! Please open an issue or submit a pull request for any improvements or bug fixes.

License

This project is licensed under the MIT License.