Science Score: 23.0%
This score indicates how likely this project is to be science-related based on various indicators:
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○CITATION.cff file
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○codemeta.json file
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○.zenodo.json file
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✓DOI references
Found 6 DOI reference(s) in README -
○Academic publication links
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✓Committers with academic emails
1 of 6 committers (16.7%) from academic institutions -
○Institutional organization owner
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○JOSS paper metadata
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○Scientific vocabulary similarity
Low similarity (9.2%) to scientific vocabulary
Last synced: 11 months ago
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JSON representation
Repository
https://celehs.github.io/PheCAP/
Statistics
- Stars: 21
- Watchers: 2
- Forks: 1
- Open Issues: 0
- Releases: 0
Created over 7 years ago
· Last pushed about 5 years ago
Metadata Files
Readme
README.Rmd
---
output: github_document
---
# PheCAP: High-Throughput Phenotyping with EHR using a Common Automated Pipeline
[](https://CRAN.R-project.org/package=PheCAP)
## Overview
The PheCAP package implements surrogate-assisted feature extraction (SAFE) and common machine learning approaches to train and validate phenotyping models. PheCAP begins with data from the EMR, including structured data and information extracted from the narrative notes using natural language processing (NLP). The standardized steps integrate automated procedures, which reduce the level of manual input, and machine learning approaches for algorithm training.
## Installation
Install stable version from CRAN:
```{r, eval=FALSE}
install.packages("PheCAP")
```
Install development version from GitHub:
```{r, eval=FALSE}
# install.packages("remotes")
remotes::install_github("celehs/PheCAP")
```
## Getting Started
Follow the [main steps](https://celehs.github.io/PheCAP/articles/main.html), and try the R codes from the [simulated data](https://celehs.github.io/PheCAP/articles/example1.html) and [real EHR data](https://celehs.github.io/PheCAP/articles/example2.html) examples.
## Citations
- Yichi Zhang`*`, Tianrun Cai`*`, Sheng Yu`*`, Kelly Cho, Chuan Hong, Jiehuan Sun, Jie Huang, Yuk-Lam Ho, Ashwin Ananthakrishnan, Zongqi Xia, Stanley Shaw, Vivian Gainer, Victor Castro, Nicholas Link, Jacqueline Honerlaw, Selena Huang, David Gagnon, Elizabeth Karlson, Robert Plenge, Peter Szolovits, Guergana Savova, Susanne Churchill, Christopher O'Donnell, Shawn Murphy, J Michael Gaziano, Isaac Kohane, Tianxi Cai`*`, and Katherine Liao`*`. [Methods for High-throughput Phenotyping with Electronic Medical Record Data Using a Common Semi-supervised Approach (PheCAP)](https://doi.org/10.1038/s41596-019-0227-6). _Nature Protocols_ (2019). `*`contributed equally.
- Yu, S., Chakrabortty, A., Liao, K. P., Cai, T., Ananthakrishnan, A. N., Gainer, V. S., … Cai, T. [Surrogate-assisted feature extraction for high-throughput phenotyping](https://doi.org/10.1093/jamia/ocw135). _Journal of the American Medical Informatics Association_ (2017), e143-e149.
- Liao, K. P., Cai, T., Savova, G. K., Murphy, S. N., Karlson, E. W., Ananthakrishnan, A. N., … Kohane, I. [Development of phenotype algorithms using electronic medical records and incorporating natural language processing](https://doi.org/10.1136/bmj.h1885). _BMJ_ (2015), 350(apr24 11), h1885–h1885.
Owner
- Name: CELEHS
- Login: celehs
- Kind: user
- Location: Boston, USA
- Website: https://celehs.hms.harvard.edu
- Repositories: 15
- Profile: https://github.com/celehs
Translational Data Science Center for a Learning Health System
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Committers
Last synced: over 2 years ago
Top Committers
| Name | Commits | |
|---|---|---|
| Ubuntu | u****u@i****l | 36 |
| BioStatStudio | h****g@g****m | 21 |
| celehs | t****i@h****u | 11 |
| Translational Data Science Center for a Learning Health System | 4****s | 11 |
| Chuan | h****h@g****m | 7 |
| Ubuntu | u****u@i****l | 1 |
Committer Domains (Top 20 + Academic)
Issues and Pull Requests
Last synced: about 1 year ago
All Time
- Total issues: 0
- Total pull requests: 0
- Average time to close issues: N/A
- Average time to close pull requests: N/A
- Total issue authors: 0
- Total 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
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
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- Average comments per issue: 0
- Average comments per pull request: 0
- Merged pull requests: 0
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Packages
- Total packages: 1
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Total downloads:
- cran 133 last-month
- Total dependent packages: 0
- Total dependent repositories: 0
- Total versions: 2
- Total maintainers: 1
cran.r-project.org: PheCAP
High-Throughput Phenotyping with EHR using a Common Automated Pipeline
- Homepage: https://celehs.github.io/PheCAP/
- Documentation: http://cran.r-project.org/web/packages/PheCAP/PheCAP.pdf
- License: GPL-3
-
Latest release: 1.2.1
published almost 6 years ago
Rankings
Stargazers count: 12.2%
Forks count: 17.8%
Dependent packages count: 29.8%
Dependent repos count: 35.5%
Average: 35.9%
Downloads: 84.1%
Maintainers (1)
Last synced:
11 months ago
Dependencies
DESCRIPTION
cran
- R >= 3.3.0 depends
- RMySQL * imports
- glmnet * imports
- graphics * imports
- methods * imports
- stats * imports
- utils * imports
- e1071 * suggests
- ggplot2 * suggests
- knitr * suggests
- randomForestSRC * suggests
- rmarkdown * suggests
- xgboost * suggests