/ColonoscopyDetection

The Health Analytics department from a very well-known hospital located in a European country has started a project to improve the results of the diagnosis related to colonoscopies. The project consists of highlighting certain areas of video frames of a colonoscopy that might be considered more relevant for colorectal illnesses due to the texture of the image in them. WIth this project we are trying to predict relevance of each image to the desease identification.

Primary LanguageJupyter NotebookMIT LicenseMIT

ColonoscopyDetection

The Health Analytics department from a very well-known hospital located in a European country has started a project to improve the results of the diagnosis related to colonoscopies. The project consists of highlighting certain areas of video frames of a colonoscopy that might be considered more relevant for colorectal illnesses due to the texture of the image in them. WIth this project we are trying to predict relevance of each image to the desease identification.

Technical report, including the following sections: Scope.

  • Descriptive analysis.
  • Data exploration.
  • Data preparation.
  • Model learning.
  • Model evaluation.

Also:

  • Any code that you might have used for procedures regarding data management (data preparation, cleaning, integration, etc.) and modelling.
  • A README document where you explain what files you delivered and the description of each one.