Unsupervised deep learning reveals prognostically relevant subtypes of glioblastoma

被引:0
|
作者
Jonathan D. Young
Chunhui Cai
Xinghua Lu
机构
[1] University of Pittsburgh,Department of Biomedical Informatics
[2] University of Pittsburgh,Intelligent Systems Program
[3] University of Pittsburgh,Center for Causal Discovery
来源
关键词
Deep learning; Unsupervised learning; Cancer; Glioblastoma multiforme; Deep belief network; Gene expression; Model selection;
D O I
暂无
中图分类号
学科分类号
摘要
引用
收藏
相关论文
共 50 条
  • [1] Unsupervised deep learning reveals prognostically relevant subtypes of glioblastoma
    Young, Jonathan D.
    Cai, Chunhui
    Lu, Xinghua
    BMC BIOINFORMATICS, 2017, 18
  • [2] UNSUPERVISED MACHINE LEARNING ON TUMOR IMMUNE TRANSCRIPTOMIC DATA REVEALS DISTINCT IMMUNOLOGIC SUBTYPES OF GLIOBLASTOMA
    Haddad, Alexander F.
    Chen, Jia Shu
    Perera, Sudheesha
    Reddy, Anvith
    Ambati, Vardhaan
    Aghi, Manish
    NEURO-ONCOLOGY, 2022, 24 : 119 - 119
  • [3] Unsupervised machine learning reveals risk stratifying glioblastoma tumor cells
    Leelatian, Nalin
    Sinnaeve, Justine
    Mistry, Akshitkumar M.
    Barone, Sierra M.
    Brockman, Asa A.
    Diggins, Kirsten E.
    Greenplate, Allison R.
    Weaver, Kyle D.
    Thompson, Reid C.
    Chambless, Lola B.
    Mobley, Bret C.
    Ihrie, Rebecca A.
    Irish, Jonathan M.
    ELIFE, 2020, 9 : 1 - 28
  • [4] Molecular Profiling Reveals Prognostically Significant Subtypes of Canine Lymphoma
    Frantz, A. M.
    Sarver, A. L.
    Ito, D.
    Phang, T. L.
    Karimpour-Fard, A.
    Scott, M. C.
    Valli, V. E. O.
    Lindblad-Toh, K.
    Burgess, K. E.
    Husbands, B. D.
    Henson, M. S.
    Borgatti, A.
    Kisseberth, W. C.
    Hunter, L. E.
    Breen, M.
    O'Brien, T. D.
    Modiano, J. F.
    VETERINARY PATHOLOGY, 2013, 50 (04) : 693 - 703
  • [5] JOINT LEARNING OF IMAGING AND GENOMIC DATA REVEALS DISTINCT GLIOBLASTOMA SUBTYPES
    Guo, Jun
    Kazerooni, Anahita Fathi
    Akbari, Hamed
    Toorens, Erik
    Sako, Chiharu
    Mamourian, Elizabeth
    Koumenis, Constantinos
    Bagley, Stephen
    Binder, Zev A.
    Lustig, Robert
    O'Rourke, Donald
    Ganguly, Tapan
    Bakas, Spyridon
    Nasrallah, MacLean
    Davatzikos, Christos
    NEURO-ONCOLOGY, 2022, 24 : 171 - 171
  • [6] Deep learning algorithm reveals two prognostic subtypes in patients with gliomas
    Jing Tian
    Mingzhen Zhu
    Zijing Ren
    Qiang Zhao
    Puqing Wang
    Colin K. He
    Min Zhang
    Xiaochun Peng
    Beilei Wu
    Rujia Feng
    Minglong Fu
    BMC Bioinformatics, 23
  • [7] LINKING HISTOLOGICAL GLIOBLASTOMA PHENOTYPES TO TRANSCRIPTIONAL SUBTYPES AND PROGNOSIS USING DEEP LEARNING
    Roetzer-Pejrimovsky, Thomas
    Kiesel, Barbara
    Nenning, Karl-Heinz
    Klughammer, Johanna
    Rajchl, Martin
    Bock, Christoph
    Hainfellner, Johannes
    Baumann, Bernhard
    Langs, Georg
    Woehrer, Adelheid
    NEURO-ONCOLOGY, 2022, 24 : 118 - 119
  • [8] Deep learning algorithm reveals two prognostic subtypes in patients with gliomas
    Tian, Jing
    Zhu, Mingzhen
    Ren, Zijing
    Zhao, Qiang
    Wang, Puqing
    He, Colin K.
    Zhang, Min
    Peng, Xiaochun
    Wu, Beilei
    Feng, Rujia
    Fu, Minglong
    BMC BIOINFORMATICS, 2022, 23 (01)
  • [9] Deep learning identified glioblastoma subtypes based on internal genomic expression ranks
    Mao, Xing-gang
    Xue, Xiao-yan
    Wang, Ling
    Lin, Wei
    Zhang, Xiang
    BMC CANCER, 2022, 22 (01)
  • [10] A Deep Learning-Based Framework for Supporting Clinical Diagnosis of Glioblastoma Subtypes
    Munquad, Sana
    Si, Tapas
    Mallik, Saurav
    Das, Asim Bikas
    Zhao, Zhongming
    FRONTIERS IN GENETICS, 2022, 13