The Drug Efficacy and Safety Analysis repository contains data and code used to analyze the efficacy and safety of drugs. The repository provides a framework for conducting drug efficacy and safety analysis by integrating data from clinical trials and post-market surveillance to evaluate the effectiveness and safety of drugs. The analysis results can help to inform drug development and improve patient outcomes.
The repository contains the following files and directories:
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Data: This directory contains the raw data used in the analysis, including clinical trial data and post-market surveillance data.
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Code: This directory contains the code used to conduct the analysis. The code is written in Python and includes scripts for data cleaning, data analysis, and visualization.
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Results: This directory contains the results of the analysis, including tables and graphs that summarize the efficacy and safety of the drugs.
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Documentation: This directory contains documentation on the analysis methods, data sources, and code.
To use the Drug Efficacy and Safety Analysis repository, follow these steps:
- Clone the repository to your local machine using
https://github.com/AnthonyByansi/DrugEfficacySafetyAnalysis.git - Navigate to the Code directory using the command line.
- Run the data cleaning scripts to prepare the data for analysis.
- Run the data analysis scripts to analyze the data and generate the results.
- View the results in the Results directory.
The code in this repository requires the following dependencies:
- Python 3.6 or higher
- Pandas
- NumPy
- Matplotlib
- Seaborn
- Scikit-learn
If you would like to contribute to the Drug Efficacy and Safety Analysis repository, please follow these steps:
- Fork the repository to your own GitHub account.
- Create a new branch in your fork for your changes.
- Make your changes to the code or documentation.
- Commit your changes and push them to your fork.
- Create a pull request to merge your changes into the main repository.
The Drug Efficacy and Safety Analysis repository is licensed under the MIT License. Please see the LICENSE file for more information.