🧬 Non-linear feature reduction using Deep Autoencoders and Breast Cancer classification.

Related tags

Deep Learning non-linearfeature-reduction-and-breast-cancer-prediction
Overview

Project summary

This repository contains the implementation of my bachelor degree project. The aim of the project is to apply non-linear feature reduction through deep autoencoders to 2 kinds of datasets obtained from two different genomic profiling technique: RNASeq and Microarray. The reduced datasets will be used to create models that predict clinical data, such the breast cancer subtype, with high accuracy. The following image represent a (much) smaller example of (one type of) the deep autoencoder architecture. You can read more on the thesis, inside the thesis folder.

Steps to reproduce

In order to get the datasets, mail me. Then:

  • Unzip each dataset
  • Put the NGS dataset content inside datasets/ngs
  • Put the microarray dataset content inside datasets/microarray

The you can reproduce all the steps from the thesis using the notebooks. I recommend to examine the notebooks in the specified order (check the index from the file name).

Confusion matrices preview

Author

  • Dr. Puglisi Lemuel @ DMI, UniCT
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