Enhanced thyroid disease prediction using ensemble machine learning: a high-accuracy approach with feature selection and class balancing

Enhanced thyroid disease prediction using ensemble machine learning: a high-accuracy approach with feature selection and class balancing

Abstract Thyroid disorders are increasingly prevalent, making early detection crucial for reducing mortality and complications. Accurate prediction of disease progression and understanding the interplay of clinical features are essential for effective diagnosis and treatment. Our study addresses the...

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Bibliographic Details
Main Authors: Md. Rezaul Islam, Aniruddha Islam Chowdhury, Sharmin Shama, Md. Masudul Hasan Lamyea
Format: Article
Language:English
Published: Springer 2025-01-01
Series:Discover Artificial Intelligence
Subjects:
Thyroid Disease Prediction
Machine Learning Algorithms
Data Visualization
Class balancing techniques
XGBoost Algorithm
Confusion Matrices
Online Access:https://doi.org/10.1007/s44163-025-00225-9
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