Build medical knowledge graph based on Unified Medical Language System (UMLS)
Project description
UMLS-Graph
This toolkit aims to leverage biomedical concepts and their relationships in Unified Language Medical System (UMLS).
Prerequisite
Install MySQL Server 5.6 and import UMLS data into MySQL database. Please refer to UMLS websites on how to install the UMLS database.
Installation
pip install umls-graph
Let Codes Speak
from umls_graph.dataset import make_umls_all
# MySQL database information
mysql_info = {}
mysql_info["database"] = "umls"
mysql_info["username"] = "root"
mysql_info["password"] = "{not gonna tell you}"
mysql_info["hostname"] = "localhost"
# read all UMLS tables and save them to csv formatted files in a folder
make_umls_all(mysql_info=mysql_info,save_folder="umls_datasets")
License
The umls-graph
project is provided by Donghua Chen.
NOTE: This project DOES NOT attach UMLS datasets due to the license issue. In addition, the processed data are not verified in actual clinical use. Please be responsible for any use.
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
umls-graph-0.0.3a1.tar.gz
(32.6 kB
view hashes)
Built Distribution
Close
Hashes for umls_graph-0.0.3a1-py3-none-any.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | d29426790f79f86cf9ce715d848d74a1d1328c8d65a3328d19c4f051f42573f9 |
|
MD5 | 6455d2d92a36e0cdebe58685de115ffd |
|
BLAKE2b-256 | a80987a2ededc1e02e3c1f3c43a7cce73f68a1d4245c3f17e29dfed215be8cc8 |