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Resources for BMIF 300qc

Tools for Downstream Analysis

  1. ONCE: A feature generation app that identifies related NLP and codified features based on an input or target disease. For example: PheCodes and CUIs.

  2. KESER Network: A tool to identify and visualize codified concepts relevant to diseases, medications, and procedures (e.g., PheCodes, RxNorm).

  3. NILE: An NLP tool for fast and efficient processing of clinical notes to UMLS CUIs. Note: You will need a UMLS License to use this tool.

  4. PETEHR: Python toolkit for EHR processing developed specifically for this tutorial. It is designed to process MIMIC-IV data and generate research-ready datasets.

 

Accessing Jupyter Notebook on O2 from your local machine

Follow the steps below to set up and access a Jupyter Notebook running on the o2 server from your local machine.

1. Prerequisites

Ensure that X11 forwarding is active on your system:

2. Set Up Local Port Forwarding

On your local machine, run the following command to log in to the o2 server and set up port forwarding:

ssh -Y -L 50001:127.0.0.1:50001 o2_username@o2

3. Request an Interactive Session

After logging into o2, request an interactive compute node enabling X11 forwarding and setting up a network tunnelby running:

srun -t 0-00:40 --pty -p interactive --mem=12G --x11 --tunnel 50001:50001 /bin/bash

4. Navigate to Your Workspace and Activate Conda

cd /n/scratch/users/v/va67/EHR_TUTORIAL_WORKSPACE
source activate ehr_tutorial

4. Start the Jupyter Notebook Server on O2

jupyter notebook --port=50001 --browser="none"

5. Access the Jupyter Notebook on your Local Machine

Open a browser and go to http://localhost:50001/tree

6. Shut Down the Jupyter Server

Once you are done, you can stop the Jupyter Notebook server by returning to the terminal where it is running and press: Ctrl+C

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A Pipeline for Processing EHR Data

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