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EndoregDB - Professional Data Infrastructure for Clinical Research

EndoregDB is a comprehensive database framework designed to manage medical and research-related data for clinical trials. This repository focuses on efficient data processing, automated deployment, security, and reproducibility, offering a flexible setup for local development environments as well as distributed systems. It supports the integration of AI/ML tools and advanced image and report processing.

This infrastructure was originally designed for clinical research studies and is optimized for handling large data volumes, including:

  • Medical reports,
  • Patient imaging and video data,
  • Clinical product and treatment data, and more.

🚀 Key Features

System Architecture

  • Modular Design: Built on scalable and reusable components to simplify integration into various environments.
  • Multi-System Support: Manages configurations for local workstations and production servers.
  • Role-Specific Configuration: Predefined roles for common use cases:
    • Medical data processing systems
    • AI/ML model deployment
    • Research workstation configuration

Security & Data Management

  • Data Encryption: All sensitive data is encrypted, and privacy policies are enforced.
  • Impermanence: Stateless system configuration with persistence for critical data.
  • Access Control: Role-based access and identity management integration.

Data and Processing Environment

  • Data Processing: Optimized for processing medical datasets with preprocessing tools.
  • AI/ML Support:
    • Integration of machine learning tools for predictive analysis.
    • TensorFlow, PyTorch, and other frameworks supported for model training.
  • Image/Video Processing: Support for analyzing patient images and clinical videos.

Development Tools & Infrastructure

  • Data Science Toolchains: Pre-configured environments for data processing, analysis, and visualization.
  • Monitoring & Logging: Setup for continuous monitoring and logging to ensure system stability and performance.

🛠 Getting Started

Prerequisites

  • A Linux-based system (Ubuntu/Debian recommended) or NixOS
  • Hardware with sufficient storage for data processing (at least 1 TB recommended)

Quick Start

  1. Clone the repository:

    git clone https://github.com/wg-lux/endoreg-db.git
cd endoreg-db

  2. Set up your Python environment: TODO: Explain Devenv / point to other docs

    direnv allow

  3. Run tests: Call Devenv Script to run tests

    runtests

📁 Repository Structure

endoreg-db/
├── endoreg_db/                # Main Django app for medical data
│   ├── case_generator/        # Sample case generator
│   ├── data/                  # Medical knowledge base
│   ├── management/            # Data wrangling operations
│   ├── models/                # Data models
│   ├── migrations/            # Database migrations
│   └── serializers/           # Serializers for data
├── .gitignore                 # Git ignore file for unnecessary files
└── README.md                  # Project description and setup instructions

🔒 Security Features

  • Data Encryption: All sensitive patient data is encrypted.
  • Role-Based Access Control: Configurable roles for managing access to various parts of the system.
  • Logging & Auditing: Comprehensive logging system that tracks user activities and data changes.

🖥️ Supported Systems

  • Workstations: Local development or research workstations with low data processing demands.
  • Servers: Scalable server infrastructure for processing large data volumes, integrated with cloud services for scalability.

🛟 Support

For issues and questions:

  • Create an issue in the repository
  • Review the Deployment Guide for common issues

📜 License

MIT - see LICENSE