Development of a cancer detection federated learning model for healthquay

Author

Fitó Alonso, Marta

Abstract

This work consists of creating a Federated Learning Model for the company HealthQuay. The model will be used to predict whether tumors are malignant or benign and will be used as a framework for future development of algorithms to predict optimal cancer treatments. A database containing information on breast cancer tumors has been used. Prior to the development of the Federated Learning Model, an exploratory analysis of the data has been carried out to visualize the existing relationships between them. Subsequently, supervised Machine Learning models have been applied to the database to see their characteristics and behavior. Finally, the Federated Learning Model has been created and trained.

 

Director

Fernández Esmerats, Joan

Degree

IQS SE - Master’s Degree in Industrial Engineering

Date

2020-05-01