Enhancing Cervical Cancer Detection And Robust Classification Through A Fusion Of Deep Learning Models

This article explores the use of machine learning algorithms and hybrid techniques to diagnose cervical cancer at an early stage. The author trained a model using a dataset from UCI and employed various feature selection methods to achieve high accuracy rates. Additionally, deep learning is proposed as a pivotal tool in two distinct approaches for classifying cervical cancer images.