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Cancer Colorectal Prediction - Machine Learning Models

Description

This repository contains the code and documentation for my two-month internship project in 2021, where I worked on predictive analysis in patients with colorectal cancer. The main objective of the project was to develop machine learning models for predicting complications during surgery. The project involved feature engineering, descriptive and predictive analysis of colorectal cancer, and the development of a graphical user interface.

Project Description

The project focuses on developing machine learning models for predicting complications in patients undergoing colorectal surgery. The project's main tasks included data preparation, cleaning, and visualization, feature engineering (dimensionality reduction), and developing predictive models. Additionally, a graphical user interface was created to enhance the usability of the models.

Features

The project includes the following features:

  • Data preparation, cleaning, and visualization
  • Feature engineering (dimensionality reduction)
  • Development of predictive models for surgical complications
  • Creation of a graphical user interface

Notebooks

The notebook "Features_Engineering [All_techniques_tried].ipynb" : All techniques i've tried

The notebook "ACP + VotingClassifier.ipynb" : The final version of the project.

The notebook "Interface graphique - Cancer colorectal.ipynb" : This notebook contains a code for preprocessing the input & also the user interface code

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