Cervical Cancer Diagnosis Using Stacked Ensemble Model and Optimized Feature Selection: An Explainable Artificial Intelligence Approach

Cervical Cancer Diagnosis Using Stacked Ensemble Model and Optimized Feature Selection: An Explainable Artificial Intelligence Approach

Cervical cancer affects more than half a million women worldwide each year and causes over 300,000 deaths. The main goals of this paper are to study the effect of applying feature selection methods with stacking models for the prediction of cervical cancer, propose stacking ensemble learning that co...

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Bibliographic Details
Main Authors: Abdulaziz AlMohimeed, Hager Saleh, Sherif Mostafa, Redhwan M. A. Saad, Amira Samy Talaat
Format: Article
Language:English
Published: MDPI AG 2023-10-01
Series:Computers
Subjects:
cervical cancer
stacking ensemble
explainable AI (XAI)
Online Access:https://www.mdpi.com/2073-431X/12/10/200

Internet

https://www.mdpi.com/2073-431X/12/10/200

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