Ensemble Learning Approach Reveals Significant Clinical Attributes from Real-World Breast Cancer Cases

Ensemble Learning Approach Reveals Significant Clinical Attributes from Real-World Breast Cancer Cases

Breast cancer has become on of the leading causes of death in Indonesia. This study contributes to global efforts to combat breast cancer by improving patient outcome prediction accuracy. This study employed ensemble learning techniques such as Random Forest, XGBoost, and LightGBM. The results of t...

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Bibliographic Details
Main Authors:	Angga Aditya Permana, Muhammad Fahrury Romdendine
Format:	Article
Language:	English
Published:	Universitas Islam Raden Rahmat 2024-04-01
Series:	G-Tech
Subjects:	Breast cancer Ensemble learning Machine learning Patient's outcome prediction Clinical data analysis
Online Access:	https://ejournal.uniramalang.ac.id/index.php/g-tech/article/view/4044

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