Gene Expression Machine Learning Models Classify Pediatric AML Subtypes with High Performance

被引：0
|
作者：
Shah, Krish [1 ]
Ma, Jing [2 ]
Djekidel, Mohamed [1 ]
Song, Guangchun [2 ]
Umeda, Masayuki [2 ]
Fan, Yiping [1 ]
Wu, Gang [1 ]
Klco, Jeffery [2 ]
机构：
[1] St Jude Childrens Res Hosp, 332 N Lauderdale St, Memphis, TN 38105 USA
[2] St Jude Childrens Res Hosp, Dept Pathol, 332 N Lauderdale St, Memphis, TN 38105 USA
来源：
BLOOD | 2023年 / 142卷
关键词：
D O I：
10.1182/blood-2023-189450
中图分类号：
R5 [内科学];
学科分类号：
1002 ; 100201 ;
摘要：
引用
收藏
页数：3
相关论文
共 50 条
  • [21] Gene expression data classification using topology and machine learning models
    Dey, Tamal K.
    Mandal, Sayan
    Mukherjee, Soham
    BMC BIOINFORMATICS, 2022, 22 (SUPPL 10)
  • [22] Machine learning based refined differential gene expression analysis of pediatric sepsis
    Mostafa Abbas
    Yasser EL-Manzalawy
    BMC Medical Genomics, 13
  • [23] Machine Learning Models for High Explosive Crystal Density and Performance
    Davis, Jack V.
    Marrs, Frank W.
    Cawkwell, Marc J.
    Manner, Virginia W.
    CHEMISTRY OF MATERIALS, 2024, 36 (22) : 11109 - 11118
  • [24] Machine learning based refined differential gene expression analysis of pediatric sepsis
    Abbas, Mostafa
    EL-Manzalawy, Yasser
    BMC MEDICAL GENOMICS, 2020, 13 (01)
  • [25] Predictive biomarkers and molecular subtypes in DLBCL: insights from PCD gene expression and machine learning
    Tiantian He
    Jie Geng
    Chuandong Hou
    Hongyi Li
    Hong Zhang
    Peng Zhao
    Peifeng He
    Xuechun Lu
    Discover Oncology, 16 (1)
  • [26] Gene expression profiling of pediatric acute myeloid leukemia (AML).
    Ross, ME
    Mahfouz, R
    Liu, HC
    Zhou, XD
    Song, GC
    Shurtleff, SA
    Girtman, K
    Williams, K
    Liang, DC
    Rubnitz, J
    Shih, LY
    Riberio, RC
    Pui, CH
    Raimondi, SC
    Downing, JR
    BLOOD, 2003, 102 (11) : 173A - 173A
  • [27] Identification of a gene expression signature associated with pediatric AML prognosis
    Yagi, T
    Morimoto, A
    Eguchi, M
    Hibi, S
    Sako, M
    Ishii, E
    Mizutani, S
    Imashuku, S
    Ohki, M
    Ichikawa, H
    BLOOD, 2003, 102 (05) : 1849 - 1856
  • [28] Gene expression signatures identify AML subtypes with recurring genetic aberrations.
    Kohlmann, A
    Schoch, C
    Dugas, M
    Schnittger, S
    Hiddemann, W
    Kern, W
    Haferlach, T
    BLOOD, 2003, 102 (11) : 362A - 362A
  • [29] Using Machine Learning to Classify the "Goodness" of Hmsc-Derived and AML-Derived EV's
    Nwizu, Chibuikem Chukwudalu
    Crawford, Lorin
    Borgovan, Theo
    Wen, Sicheng
    Dooner, Mark S.
    Egan, Pamela C.
    Reagan, John L.
    Olszewski, Adam J.
    Goldberg, Laura R.
    Quesenberry, Peter J.
    BLOOD, 2018, 132
  • [30] Using comprehensive machine-learning models to classify complex morphological characters
    Teng, Dequn
    Li, Fengyuan
    Zhang, Wei
    ECOLOGY AND EVOLUTION, 2021, 11 (15): : 10421 - 10431
12345