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Code and data for reproducing key results in the paper "Utility of Machine-Learning Approaches to Identify Behavioral Markers for Substance Use Disorders: Impulsivity Dimensions as Predictors of Current Cocaine Dependence".

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Cocaine Dependence

Project Status: Inactive - The project has reached a stable, usable state but is no longer being actively developed; support/maintenance will be provided as time allows.DOI

Code and data for reproducing key results in the paper "Utility of Machine-Learning Approaches to Identify Behavioral Markers for Substance Use Disorders: Impulsivity Dimensions as Predictors of Current Cocaine Dependence".

See the Python and R directories for their respective instructions on installation and reproducing the results.

Installation

You can install the latest development version from github with:

git clone https://github.com/CCS-Lab/cocaine-dependence.git

If you encounter a clear bug, please file a minimal reproducible example on github.

Citation

If you found our work useful please cite us in your work:

@Article{10.3389/fpsyt.2016.00034,
         Author = {Ahn, Woo-Young and Ramesh, Divya and Moeller, Frederick Gerard and Vassileva, Jasmin},
         Title = {Utility of Machine-Learning Approaches to Identify Behavioral Markers for Substance Use Disorders: Impulsivity Dimensions as Predictors of Current Cocaine Dependence}, 
         Journal = {Frontiers in Psychiatry}, 
         Volume = {7}, 
         Pages = {34}, 
         Year = {2016}, 
         URL = {http://journal.frontiersin.org/article/10.3389/fpsyt.2016.00034}, 
         DOI = {10.3389/fpsyt.2016.00034}, 
         ISSN = {1664-0640},   
}

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Code and data for reproducing key results in the paper "Utility of Machine-Learning Approaches to Identify Behavioral Markers for Substance Use Disorders: Impulsivity Dimensions as Predictors of Current Cocaine Dependence".

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