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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Bibliographische Detailangaben
Veröffentlicht in:	Leukemia research 2024-06, Vol.141, p.107502-107502, Article 107502
Hauptverfasser:	Zad, Zahra, Bonecker, Simone, Wang, Taiyao, Zalcberg, Ilana, Stelzer, Gustavo T., Sabioni, Bruna, Gutiyama, Luciana Mayumi, Fleck, Julia L., Paschalidis, Ioannis Ch
Format:	Artikel
Sprache:	eng
Schlagworte:	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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Beschreibung
Zusammenfassung:	•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