SNOMED Ontology Parser

A Python tool for extracting medical concepts from text and mapping them to the SNOMED-CT ontology hierarchy.

Overview

This repository provides functionality to:

• Extract medical concepts from text documents
• Map extracted concepts to SNOMED-CT ontology
• Analyze concept distributions across different hierarchical levels
• Visualize concept relationships and distributions

Prerequisites

1. Required Python Packages

Install the following packages with their specific versions:

• scispacy (v0.5.1)
• medspacy (v0.2.0.0)
• Owlready2 (v0.37) - Required for pymedtermino2

2. UMLS and SNOMED-CT Access

1. Apply for UMLS access at the UMLS website
2. Download the required UMLS and SNOMED-CT files
3. Follow the setup instructions in the pymedtermino2 documentation

Installation

1. Clone this repository:

git clone https://github.com/yourusername/snomed-ontology-parser.git
cd snomed-ontology-parser

2. Create and activate the conda environment:

conda env create -f environment.yml
conda activate snomed-parser

Usage

Running the Analysis

1. Place your UMLS data files in the ./data directory
2. Run the Jupyter notebook:

jupyter notebook concept_distribution.ipynb

Note: If you encounter a locked pym.sqlite file error, use the provided script:

bash remove_sql_lock.sh

Finding Concept IDs

To look up specific concept IDs, you can use the SNOMED CT Browser (Note: The browser may use an older version of the SNOMED ontology)

Example

Input text:

Alterations in the hypocretin receptor 2 and preprohypocretin genes produce narcolepsy in some animals.

Output visualization:

Project Structure

snomed-ontology-parser/
├── src/
│   ├── main.py              # Main application entry point
│   ├── concept_extractor.py # Extracts medical concepts from text
│   ├── concept_analyzer.py  # Analyzes concept distributions
│   └── data_loader.py       # Handles UMLS data loading
├── data/                    # Directory for UMLS data files
├── concept_distribution.ipynb
├── environment.yml
└── remove_sql_lock.sh