Improving Prediction of Cervical Cancer Using KNN Imputed SMOTE Features and Multi-Model Ensemble Learning Approach

Improving Prediction of Cervical Cancer Using KNN Imputed SMOTE Features and Multi-Model Ensemble Learning Approach

<b>Objective:</b> Cervical cancer ranks among the top causes of death among females in developing countries. The most important procedures that should be followed to guarantee the minimizing of cervical cancer’s aftereffects are early identification and treatment under the finest medical...

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Bibliographic Details
Main Authors: Hanen Karamti, Raed Alharthi, Amira Al Anizi, Reemah M. Alhebshi, Ala’ Abdulmajid Eshmawi, Shtwai Alsubai, Muhammad Umer
Format: Article
Language:English
Published: MDPI AG 2023-09-01
Series:Cancers
Subjects:
cervical cancer detection
missing values
healthcare
KNN imputer
SMOTE
ensemble learning
Online Access:https://www.mdpi.com/2072-6694/15/17/4412

Internet

https://www.mdpi.com/2072-6694/15/17/4412

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