Prediction of deep molecular response in chronic myeloid leukemia using supervised machine learning models

•Predicting deep molecular response to imatinib treatment for Chronic Myeloid Leukemia.•Leveraging machine learning methods.•Utilizing data from a developing country (Brazil) where cost considerations affect treatment.

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Bibliographic Details
Published in:Leukemia research 2024-06, Vol.141, p.107502-107502, Article 107502
Main Authors: Zad, Zahra, Bonecker, Simone, Wang, Taiyao, Zalcberg, Ilana, Stelzer, Gustavo T., Sabioni, Bruna, Gutiyama, Luciana Mayumi, Fleck, Julia L., Paschalidis, Ioannis Ch
Format: Article
Language:English
Subjects:
Chronic Myeloid Leukemia (CML)
Deep Molecular Response (DMR)
Humans
Imatinib (IM)
Leukemia, Myelogenous, Chronic, BCR-ABL Positive - diagnosis
Leukemia, Myelogenous, Chronic, BCR-ABL Positive - drug therapy
Leukemia, Myelogenous, Chronic, BCR-ABL Positive - genetics
Leukemia, Myelogenous, Chronic, BCR-ABL Positive - pathology
Prognosis
Supervised Machine Learning
Treatment-free remission (TFR)
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Description
Summary:•Predicting deep molecular response to imatinib treatment for Chronic Myeloid Leukemia.•Leveraging machine learning methods.•Utilizing data from a developing country (Brazil) where cost considerations affect treatment.
ISSN:0145-2126
1873-5835
DOI:10.1016/j.leukres.2024.107502