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samgep

https://celehs.github.io/SAMGEP/

https://github.com/celehs/samgep

Science Score: 23.0%

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

  • ○
    CITATION.cff file
  • ○
    codemeta.json file
  • ○
    .zenodo.json file
  • ✓
    DOI references
    Found 2 DOI reference(s) in README
  • ○
    Academic publication links
  • ✓
    Committers with academic emails
    1 of 3 committers (33.3%) from academic institutions
  • ○
    Institutional organization owner
  • ○
    JOSS paper metadata
  • ○
    Scientific vocabulary similarity
    Low similarity (7.9%) to scientific vocabulary
Last synced: 11 months ago · JSON representation

Repository

https://celehs.github.io/SAMGEP/

Basic Info
  • Host: GitHub
  • Owner: celehs
  • Language: R
  • Default Branch: main
  • Homepage:
  • Size: 47.3 MB
Statistics
  • Stars: 2
  • Watchers: 3
  • Forks: 0
  • Open Issues: 0
  • Releases: 0
Created over 5 years ago · Last pushed over 5 years ago
Metadata Files
Readme

README.Rmd 

---
output: github_document
---

# SAMGEP: A Semi-Supervised Method for Prediction of Phenotype Event Times

[![CRAN](https://www.r-pkg.org/badges/version/SAMGEP)](https://CRAN.R-project.org/package=SAMGEP)

## Overview

Leveraging large-scale electronic health record (EHR) data to estimate survival curves for clinical events can enable more powerful risk estimation and comparative effectiveness research. Semi-supervised Calibration of Risk with Noisy Event Times (SCORNET) yields a consistent and efficient survival curve estimator by leveraging a small size of current status labels and a large size of imperfect surrogate features.

![Schematic of the SAMGEP algorthm.](https://github.com/celehs/SAMGEP/blob/main/img/samgep_flowchart.png?raw=true)

## Installation

Install stable version from CRAN:

```{r, eval=FALSE}
install.packages("SAMGEP")
```

Install development version from GitHub:

```{r, eval=FALSE}
# install.packages("remotes")
remotes::install_github("celehs/SAMGEP")
```

## Citation

Semi-supervised Calibration of Risk with Noisy Event Times (SCORNET) Using Electronic Health Record Data. Yuri Ahuja, Liang Liang, Selena Huang, Tianxi Cai. bioRxiv 2021.01.08.425976; doi: https://doi.org/10.1101/2021.01.08.425976

Owner

  • Name: CELEHS
  • Login: celehs
  • Kind: user
  • Location: Boston, USA

Translational Data Science Center for a Learning Health System

GitHub Events

Total
Last Year

Committers

Last synced: over 3 years ago

All Time
  • Total Commits: 20
  • Total Committers: 3
  • Avg Commits per committer: 6.667
  • Development Distribution Score (DDS): 0.25
Top Committers
Name Email Commits
Yuri y****a@h****u 15
Ming Yang h****g@g****m 4
Translational Data Science Center for a Learning Health System 4****s@u****m 1
Committer Domains (Top 20 + Academic)
hms.harvard.edu: 1

Issues and Pull Requests

Last synced: 12 months ago

All Time
  • Total issues: 0
  • Total pull requests: 2
  • Average time to close issues: N/A
  • Average time to close pull requests: 1 minute
  • Total issue authors: 0
  • Total pull request authors: 2
  • Average comments per issue: 0
  • Average comments per pull request: 0.0
  • Merged pull requests: 2
  • Bot issues: 0
  • Bot pull requests: 0
Past Year
  • Issues: 0
  • Pull requests: 0
  • Average time to close issues: N/A
  • Average time to close pull requests: N/A
  • Issue authors: 0
  • Pull request authors: 0
  • Average comments per issue: 0
  • Average comments per pull request: 0
  • Merged pull requests: 0
  • Bot issues: 0
  • Bot pull requests: 0
View more stats
Top Authors
Issue Authors
Pull Request Authors
  • celehs (1)
  • yahuja1 (1)
Top Labels
Issue Labels
Pull Request Labels

Packages

  • Total packages: 1
  • Total downloads:
    • cran 213 last-month
  • Total dependent packages: 0
  • Total dependent repositories: 0
  • Total versions: 1
  • Total maintainers: 1
cran.r-project.org: SAMGEP

A Semi-Supervised Method for Prediction of Phenotype Event Times

  • Versions: 1
  • Dependent Packages: 0
  • Dependent Repositories: 0
  • Downloads: 213 Last month
Rankings
Stargazers count: 28.5%
Forks count: 28.8%
Dependent packages count: 29.8%
Dependent repos count: 35.5%
Average: 41.7%
Downloads: 86.2%
Maintainers (1)
Yuri_Ahuja@hms.harvard.edu
Last synced: 12 months ago

Dependencies

DESCRIPTION cran
  • R >= 3.5.0 depends
  • Rcpp * imports
  • abind * imports
  • doParallel * imports
  • foreach * imports
  • mvtnorm * imports
  • nlme * imports
  • nloptr * imports
  • pROC * imports
  • parallel * imports
  • stats * imports
  • knitr * suggests
  • rmarkdown * suggests