Best models of Tables 2–4.

<div><p>Breast cancer is a significant global health concern with rising incidence and mortality rates. Current diagnostic methods face challenges, necessitating improved approaches. This study employs various machine learning (ML) algorithms, including KNN, SVM, ANN, RF, XGBoost, ensemb...

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Bibliographic Details
Main Author:	Kazi Arman Ahmed (21567972) (author)
Other Authors:	Israt Humaira (21567975) (author), Ashiqur Rahman Khan (21567978) (author), Md Shamim Hasan (20721344) (author), Mukitul Islam (21567981) (author), Anik Roy (11688974) (author), Mehrab Karim (21567984) (author), Mezbah Uddin (21567987) (author), Ashique Mohammad (21567990) (author), Md Doulotuzzaman Xames (21567993) (author)
Published:	2025
Subjects:	Biotechnology Cancer Biological Sciences not elsewhere classified Mathematical Sciences not elsewhere classified Information Systems not elsewhere classified predicting breast cancer necessitating improved approaches improve prediction performance improve prediction accuracy breast cancer diagnosis traditional ml models models using original based ensemble strategies ensemble models ml models two stages third phases synthetic datasets study demonstrated stratified k rising incidence original dataset mortality rates model ensembles including knn gaussian copula fold cross first stage findings underscore deep learning comparative analysis based multi aiding decision
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Best models of Tables 2–4.

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