Machine Learning‐Based Prediction of β‐Thalassemia Trait Using Red Blood Cell Indices

Our findings demonstrate that ML-based models could offer a promising tool for improving β-TT detection, optimizing clinical workflows, and enhancing resource utilization in hematology.

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Publication Details

Journal
International Journal of Laboratory Hematology
Published
2025-10-15
DOI
https://doi.org/10.1111/ijlh.70017
Primary Topic
Hemoglobinopathies and Related Disorders
Type
article
Field-Weighted Citation Impact
0.00
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article

Machine Learning‐Based Prediction of β‐Thalassemia Trait Using Red Blood Cell Indices

Muslu Kazım Körez, Esra Paydaş Hataysal
International Journal of Laboratory Hematology
Hemoglobinopathies and Related Disorders
article

Machine Learning‐Based Prediction of β‐Thalassemia Trait Using Red Blood Cell Indices

Muslu Kazım Körez, Esra Paydaş Hataysal
article en

Abstract

Our findings demonstrate that ML-based models could offer a promising tool for improving β-TT detection, optimizing clinical workflows, and enhancing resource utilization in hematology.

International Journal of Laboratory HematologyVol. 48(1)
Selçuk University (TR), İstanbul Kanuni Sultan Süleyman Eğitim ve Araştırma Hastanesi (TR)
Openalex Percentile: Top 59%
Hemoglobinopathies and Related Disorders
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Machine Learning‐Based Prediction of β‐Thalassemia Trait Using Red Blood Cell Indices — Muslu Kazım Körez, Esra Paydaş Hataysal · International Journal of Laboratory Hematology (2025) | TGRS Research Map | TGRS