Using AI to improve the molecular classification of brain tumors

被引:0
|
作者
机构
来源
Nature Medicine | 2023年 / 29卷
关键词
D O I
暂无
中图分类号
学科分类号
摘要
We used deep neural networks trained on optical histology and open-source genomic data to predict the molecular genetics of brain tumors during surgery. Our results represent how AI-based diagnostics can provide a valuable adjunct to wet laboratory methods for molecular testing in patients with cancer.
引用
收藏
页码:793 / 794
页数:1
相关论文
共 50 条
  • [41] Computer assisted classification of brain tumors
    Roehrl, Norbert
    Iglesias-Rozas, Jose R.
    Weidl, Galia
    DATA ANALYSIS, MACHINE LEARNING AND APPLICATIONS, 2008, : 55 - +
  • [42] The new WHO classification of brain tumors
    Smirniotopoulos, JG
    NEUROIMAGING CLINICS OF NORTH AMERICA, 1999, 9 (04) : 595 - +
  • [43] New WHO Classification of Brain Tumors
    Thurnher, M. M.
    NEURORADIOLOGY JOURNAL, 2008, 21 : 14 - 16
  • [44] CLASSIFICATION OF BRAIN TUMORS AND EXPERIMENTAL MODELS
    LISS, L
    PROGRESS IN EXPERIMENTAL TUMOR RESEARCH, 1972, 17 : 1 - &
  • [45] The revised WHO classification of brain tumors
    Michotte, A
    ACTA NEUROLOGICA BELGICA, 1996, 96 (02): : 85 - 88
  • [46] Risk assignment in childhood brain tumors: the emerging role of molecular and biologic classification.
    Pollack I.F.
    Biegel J.
    Yates A.
    Hamilton R.
    Finkelstein S.
    Current Oncology Reports, 2002, 4 (2) : 114 - 122
  • [48] Molecular cytogenetics of brain tumors
    Bigner, SH
    Schrock, E
    JOURNAL OF NEUROPATHOLOGY AND EXPERIMENTAL NEUROLOGY, 1997, 56 (11): : 1173 - 1181
  • [49] Molecular biology of brain tumors
    Kubo, O
    Takakura, K
    CRITICAL REVIEWS IN NEUROSURGERY, 1996, 6 (04) : 232 - 236
  • [50] Molecular diagnosis of brain tumors
    Ichimura, Koichi
    Nakano, Yoshiko
    Kanemura, Yonehiro
    Yoshioka, Takako
    Hirato, Junko
    Hara, Junichi
    Ichikawa, Hitoshi
    Narita, Yoshitaka
    CANCER SCIENCE, 2021, 112 : 200 - 200