This repository contains the code and resources for my diploma paper on "Cancer Detection and Classification." The goal of this project is to develop an accurate and efficient method for detecting and classifying cancer using gene expression data.

• data: This directory contains the gene expression datasets used in the project. It includes both diseased and healthy samples obtained from various sources.

• code: This directory contains the Python scripts and Jupyter notebooks used for data preprocessing, model training, and evaluation.

• models: This directory stores the trained models, including their weights and configurations.

• results: This directory contains the results and performance metrics obtained from the trained models.

• docs: This directory holds the documentation and related resources for the project.

To reproduce the experiments and run the code in this project, please ensure you have the following dependencies installed:

• Python 3.x
• Jupyter Notebook
• PyTorch
• NumPy
• Pandas
• Scikit-learn

You can install the required packages by running the following command:

Clone the repository to your local machine using the following command: bash Copy code

git clone https://github.com/your-username/GeneExpressionCancerLRP.git

Navigate to the project directory: bash Copy code

cd GeneExpressionCancerLRP

Run the Jupyter notebooks in the code directory to preprocess the data, train the models, and evaluate the performance. Trained models will be saved in the models directory, and the results will be stored in the results directory. Documentation For more detailed information about the project, including the methodology, experimental setup, and results analysis, please refer to the documentation in the docs directory.

This project is licensed under the MIT License. See the LICENSE file for more details.

I would like to express my gratitude to my advisors and mentors for their guidance and support throughout this project. I also acknowledge the contributions of the researchers and institutions whose datasets and resources were utilized in this work.

For any questions or inquiries regarding this project, please feel free to contact me at [email protected].

Feel free to customize this README file according to your specific project details, including additional sections or information that is relevant to your diploma paper.