Cervical Cancer Prediction Based on Imbalanced Data Using Machine Learning Algorithms with a Variety of Sampling Methods

Cervical Cancer Prediction Based on Imbalanced Data Using Machine Learning Algorithms with a Variety of Sampling Methods

Cervical cancer affects a large portion of the female population, making the prediction of this disease using Machine Learning (ML) of utmost importance. ML algorithms can be integrated into complex, intelligent, agent-based systems that can offer decision support to resident medical doctors or even...

Full description

Saved in:
Bibliographic Details
Main Authors: Mădălina Maria Muraru, Zsuzsa Simó, László Barna Iantovics
Format: Article
Language:English
Published: MDPI AG 2024-11-01
Series:Applied Sciences
Subjects:
cervical cancer
sampling methods
imbalanced datasets
classification methods
prediction methods
K-nearest neighbors
Online Access:https://www.mdpi.com/2076-3417/14/22/10085
Tags: Add Tag
No Tags, Be the first to tag this record!

Internet

https://www.mdpi.com/2076-3417/14/22/10085

Similar Items