AML: Predicting the Unpredictable

Koichi Takahashi

doi:10.1016/j.stem.2018.07.005

AML: Predicting the Unpredictable

Koichi Takahashi

Leukemia

Research output: Contribution to journal › Short survey › peer-review

2 Scopus citations

Abstract

Acute myeloid leukemia (AML) has been considered an unpredictable and unpreventable disease. Recently in Nature, Abelson et al. (2018) presented two models of AML risk prediction, one using the detection of high-risk age-related clonal hematopoiesis and the other using dynamic clinical attributes available from routine blood work. Acute myeloid leukemia (AML) has been considered an unpredictable and unpreventable disease. Recently in Nature, Abelson et al. (2018) presented two models of AML risk prediction, one using the detection of high-risk age-related clonal hematopoiesis and the other using dynamic clinical attributes available from routine blood work.

Original language	English (US)
Pages (from-to)	162-163
Number of pages	2
Journal	Cell Stem Cell
Volume	23
Issue number	2
DOIs	https://doi.org/10.1016/j.stem.2018.07.005
State	Published - Aug 2 2018

ASJC Scopus subject areas

Molecular Medicine
Genetics
Cell Biology

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10.1016/j.stem.2018.07.005

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title = "AML: Predicting the Unpredictable",

abstract = "Acute myeloid leukemia (AML) has been considered an unpredictable and unpreventable disease. Recently in Nature, Abelson et al. (2018) presented two models of AML risk prediction, one using the detection of high-risk age-related clonal hematopoiesis and the other using dynamic clinical attributes available from routine blood work. Acute myeloid leukemia (AML) has been considered an unpredictable and unpreventable disease. Recently in Nature, Abelson et al. (2018) presented two models of AML risk prediction, one using the detection of high-risk age-related clonal hematopoiesis and the other using dynamic clinical attributes available from routine blood work.",

author = "Koichi Takahashi",

note = "Publisher Copyright: {\textcopyright} 2018 Elsevier Inc.",

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AB - Acute myeloid leukemia (AML) has been considered an unpredictable and unpreventable disease. Recently in Nature, Abelson et al. (2018) presented two models of AML risk prediction, one using the detection of high-risk age-related clonal hematopoiesis and the other using dynamic clinical attributes available from routine blood work. Acute myeloid leukemia (AML) has been considered an unpredictable and unpreventable disease. Recently in Nature, Abelson et al. (2018) presented two models of AML risk prediction, one using the detection of high-risk age-related clonal hematopoiesis and the other using dynamic clinical attributes available from routine blood work.

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AML: Predicting the Unpredictable

Abstract

ASJC Scopus subject areas

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