Machine learning approach for differentiating iron deficiency anemia and thalassemia using random forest and gradient boosting algorithms

Machine learning approach for differentiating iron deficiency anemia and thalassemia using random forest and gradient boosting algorithms

Abstract Formulas based on red blood cell indices have been used to differentiate between iron deficiency anemia (IDA) and thalassemia (Thal). However, they exhibit varying efficiencies. In this study, we aimed to develop a tool for discriminating between IDA and Thal by using the random forest (RF)...

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Bibliographic Details
Main Authors: Wanicha Tepakhan, Wisarut Srisintorn, Tipparat Penglong, Pirun Saelue
Format: Article
Language:English
Published: Nature Portfolio 2025-05-01
Series:Scientific Reports
Subjects:
Iron deficiency anemia
Thalassemia
Machine learning
Random forest
Gradient boosting
Online Access:https://doi.org/10.1038/s41598-025-01458-5
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https://doi.org/10.1038/s41598-025-01458-5

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