mimic-iv-analysis 0.5.6

A data science and machine learning framework for nursing research

MIMIC-IV Analysis

A comprehensive analytical toolkit for exploring and modeling data from the MIMIC-IV clinical database.

Features

• Exploratory Data Analysis
• Patient Trajectory Visualization
• Order Pattern Analysis
• Predictive Modeling

Installation

Prerequisites

• Python 3.12 or higher
• pip or conda package manager

Option 1: Using pip

pip install -e ".[dev]"  # Install with development dependencies

Option 3: Manual Installation

1. Create a virtual environment:

python -m venv .venv
source .venv/bin/activate  # On Windows: .venv\Scripts\activate

2. Install dependencies:

pip install -e ".[dev]"  # Install with development dependencies

Development

Code Style

This project uses:

• black for code formatting
• isort for import sorting
• flake8 for style guide enforcement
• mypy for static type checking

To format code:

black .
isort .

To check code:

flake8 .
mypy .

Running Tests

pytest tests/
pytest --cov=mimic_iv_analysis tests/  # With coverage

Project Structure

mimic_iv_analysis/
├── src/                     # Source code directory
│   ├── __init__.py         # Package initialization
│   ├── analysis/           # Analysis modules
│   ├── data/               # Data handling modules
│   ├── core/               # Core functionality
│   ├── utils/              # Utility functions
│   └── visualization/      # Visualization modules
├── tests/                  # Test suite
│   ├── unit/              # Unit tests
│   └── integration/       # Integration tests
├── docs/                   # Documentation
├── scripts/                # Utility scripts
│   └── install.sh         # Installation script
├── setup_config/          # Configuration files
├── .env.example           # Example environment variables
├── .gitignore             # Git ignore rules
├── LICENSE                # Project license
├── pyproject.toml         # Project configuration
├── README.md              # Project documentation
└── setup.py               # Setup configuration

Usage

Run the Streamlit dashboard:

# If installed with pip:
mimic-iv

# Or directly:
streamlit run src/visualization/app.py

Contributing

1. Fork the repository
2. Create a feature branch
3. Make your changes
4. Run tests
5. Submit a pull request

License

MIT