Skip to content

ML project, EPFL 2019 - Clustering tumor patients based on hormonal response

License

Notifications You must be signed in to change notification settings

valentinoli/pdx

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

Clustering estrogen receptor-positive breast cancer tumors based on hormonal response type

Project in Machine Learning (CS-433)

EPFL, 2019

Abstract

We employ unsupervised machine learning techniques to cluster subtypes of estrogen receptor-positive breast cancer, which is the most common variant worldwide. Clustering is done according to hormone responses obtained from in vivo models of patient-derived xenografts. Our results facilitate more targeted treatment of patients, responding to the urgent need for personalized medicine to treat breast cancer.

Architecture

Dependencies

Data

Download here

Reproduction

  1. Clone or fork the repository
  2. Download the data and add the data/ folder to the root of the project
  3. Install Jupyter Notebook
  4. Install the abovementioned libraries
  5. Run data_analysis.ipynb to reproduce the data analysis results
  6. Run cluster_analysis.ipynb to reproduce the cluster analysis results

Authors

License

This project is licensed under the MIT License - see the LICENSE file for details.

Acknowledgments

We thank Fabio De Martino, our supervisor at the BRISKEN lab, for his constant guidance and support throughout the learning process.