https://github.com/astrazeneca/ctelc-patient-attrition-model
Clinical Trial Enrollment Life Cycle (CTELC) modeling project aims to leverage "industry-wide" data to understand key drivers and build predictive models. Patient attrition, also referred to as dropout or patient withdrawal, occurs when patients enrolled in a clinical trial either withdraw or are lost to follow-up by the clinical site and trial sponsor.
https://github.com/astrazeneca/ctelc-patient-attrition-model
Last synced: 8 months ago
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Clinical Trial Enrollment Life Cycle (CTELC) modeling project aims to leverage "industry-wide" data to understand key drivers and build predictive models. Patient attrition, also referred to as dropout or patient withdrawal, occurs when patients enrolled in a clinical trial either withdraw or are lost to follow-up by the clinical site and trial sponsor.
- Host: GitHub
- URL: https://github.com/astrazeneca/ctelc-patient-attrition-model
- Owner: AstraZeneca
- License: apache-2.0
- Created: 2020-12-07T13:52:12.000Z (over 5 years ago)
- Default Branch: master
- Last Pushed: 2020-12-16T17:40:11.000Z (over 5 years ago)
- Last Synced: 2025-09-09T11:50:56.966Z (9 months ago)
- Language: R
- Homepage:
- Size: 380 KB
- Stars: 6
- Watchers: 3
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: readme.md
- License: LICENSE
Awesome Lists containing this project
README
Modeling Clinical Trial Attrition Using Machine Intelligence:
A driver analytics case study using 1,325 trials representing one million patients
---------------------------------------------------------------------------------------------------------------
This file is the readme.txt file for the code folder that contains the R code that was used in the model
TABLE OF CONTENTS
-----------------
* Full Author List
* Introduction
* Requirements
* Folder Contents
* Contact
Full Author List
----------------
Emmette Hutchison, Youyi Zhang, Sreenath Nampally, Imran Khan Neelufer, Vlad Malkov, Jim Weatherall, Faisal Khan and Khader Shameer
Introduction
------------
Patient attrition, also referred to as dropout or patient withdrawal, occurs when patients enrolled
in a clinical trial either withdraw or are lost to follow-up by the clinical site and trial sponsor.
Requirements
------------
This was performed using RStudio and R. The versions of RStudio and R are listed below:
RStudio 1.0.44, which can be downloaded from https://rstudio.com/products/rstudio/download/
R 3.5.2 (2018-12-20). RStudio can be installed from https://cran.r-project.org/mirrors.html
The project requires the following R packages. The version numbers indicate the version of the packages
that were used in the analysis. Please install the following packages using the command below in your R
Environment
SuperLearner==2.0-26
MASS==7.3-51.5
ranger==0.12.1
ipred==0.9-9
kernlab==0.9-29
arm==1.10-1
dplyr==1.4.2
caret==6.0-84
parallel==3.5.2
Folder Contents
----------------
This folder contains the data files that was used in the analysis. The file descriptions are listed below:
```
|---- readme.md : readme file for the data folder
|
|---- code : This folder contains the code required for the pre-processing of raw data and running the predictive model results,
| further explanation is available in a readme file within this folder
|
|---- data: This folder contains two sub-folders, another readme file in the folder will explain the overview on each folder content.
|---- analysis_ready
|---- requirments.txt : is a file which lists the libraries used in the model building exercise, this file can be used to install the packages needed.
|
| Using command "Install.Packages("package name") one can easily install the required packages
```
Contact
--------
shameer.khader@astrazeneca.com