radipop_scripts

Scripts to train and validate random forest model for HVPG prediction

https://github.com/menchelab/radipop_scripts

Science Score: 44.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • CITATION.cff file
    Found CITATION.cff file
  • codemeta.json file
    Found codemeta.json file
  • .zenodo.json file
    Found .zenodo.json file
  • DOI references
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    Low similarity (5.9%) to scientific vocabulary
Last synced: 8 months ago · JSON representation ·

Repository

Scripts to train and validate random forest model for HVPG prediction

Basic Info
  • Host: GitHub
  • Owner: menchelab
  • Language: Jupyter Notebook
  • Default Branch: master
  • Size: 20.3 MB
Statistics
  • Stars: 1
  • Watchers: 1
  • Forks: 0
  • Open Issues: 0
  • Releases: 0
Created over 2 years ago · Last pushed over 2 years ago
Metadata Files
Readme Citation

README.md

Radiomics-based prediction of portal hypertension severity and of liver-related events using routine CT scans of patients with cirrhosis

Hepatic venous pressure gradient (HVPG) is the reference standard to diagnose portal hypertension. Elevated HVPG is predictive of hepatic decompensation and mortality [Ripoll, 2007], and its measurement is indicated for diagnosis, therapy monitoring and risk stratification. However, HVPG measurement is invasive, relatively expensive and requires specialized medical infrastructure and expertise. Therefore, a non-invasive alternative is highly desirable.

In this project, we developed a radiomics-based model for the non-invasive determination of HVPG > 10mmHg (clinically significant portal hypertension, CSPH) from abdominal CT scans.

This work is published in <<<>>>

Code base for analysis

This codebase is organized in 3 main folders:

scripts_0preprocessing

  • clean the metadata
  • preprocess raw images
  • extract radiomics features

scripts_1ml

  • explore the feature space
  • feature selection and batch correction
  • train and optimize a random forest classifier to predict for HVPG ≥10 mmHg
  • evaluate performance of the model ### scripts_cox (Lorenz Balcar/Bernhard Scheiner)
  • preform cox regression analysis for prognosis endpoints

References

Ripoll, C. et al. Hepatic venous pressure gradient predicts clinical decompensation in patients with compensated cirrhosis. Gastroenterology 133, 481–488 (2007)

Owner

  • Name: Menche Lab
  • Login: menchelab
  • Kind: organization
  • Location: Vienna, Austria

Citation (CITATION.cff)

cff-version: 1.2.0
message: "If you use this software, please cite it as below."
authors:
- family-names: "Sin"
  given-names: "Celine"
  orcid: "https://orcid.org/0000-0002-4975-4618"
title: "radipop_analy"
version: 1.0.0
doi: ????/zenodo????
date-released: 2022-11-10
url: "https://github.com/celinesin/radipop_analy"

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Last synced: 9 months ago

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Celine Sin c****n@g****m 4

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