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vadescehr

https://github.com/jiajunqiu/vadescehr

Science Score: 49.0%

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    CITATION.cff file
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    Found 1 DOI reference(s) in README
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    Academic publication links
    Links to: medrxiv.org
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    Scientific vocabulary similarity
    Low similarity (6.3%) to scientific vocabulary
Last synced: 10 months ago · JSON representation

Repository

Basic Info
  • Host: GitHub
  • Owner: JiajunQiu
  • License: gpl-3.0
  • Language: Jupyter Notebook
  • Default Branch: main
  • Size: 144 MB
Statistics
  • Stars: 1
  • Watchers: 1
  • Forks: 0
  • Open Issues: 0
  • Releases: 3
Created almost 2 years ago · Last pushed over 1 year ago
Metadata Files
Readme License Citation

README.md

VaDeSCEHR

This repository contains code for a method for clustering longitudinal time-to-event data as extracted from electronic health records, published as a preprint on https://www.medrxiv.org/content/10.1101/2024.01.11.24301148v2

Deep representation learning for clustering longitudinal survival data from electronic health records.

Dependencies install

All the dependencies are in packages.txt based on python3.9

python3.9 -m pip install -r packages.txt

Data download and simulation data

The UKB EHR data must be downloaded from UK Biobank (https://www.ukbiobank.ac.uk/) by user's self

The 5 fold simulation data used in the paper can be found at https://github.com/JiajunQiu/VaDeSCEHR/tree/main/data/simulation

Example test

The following code can be used to re-produce the result on simulation for a single fold:

python3.9 main.py -s simulation -n ./data/simulation/benchmarkdatafold1.pkl -p outputs/outputsimulationfold1 -r False -b True -k True

And you can find the example of the outputs in https://github.com/JiajunQiu/VaDeSCEHR/tree/main/outputs/outputsimulationfold1

Owner

  • Login: JiajunQiu
  • Kind: user

GitHub Events

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  • Issues event: 1
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Last Year
  • Create event: 5
  • Issues event: 1
  • Release event: 9
  • Watch event: 5
  • Push event: 4
  • Fork event: 2