Graph deep learning detects contextual prognostic biomarkers from whole-slide images

被引:1
|
作者
Kwon, Sunghoon [1 ]
Park, Jeong Hwan [2 ]
机构
[1] Seoul Natl Univ, Seoul, South Korea
[2] Seoul Natl Univ, Coll Med, Seoul, South Korea
关键词
D O I
10.1038/s41551-022-00927-w
中图分类号
R318 [生物医学工程];
学科分类号
0831 ;
摘要
Graph deep learning can be used to detect contextual pathological features within a complex tumour microenvironment. We have shown the use of graph deep learning for predicting the prognosis of patients with tumours, and use it to identify additional contextual prognostic biomarkers for pathologists.
引用
收藏
页码:1326 / 1327
页数:2
相关论文
共 50 条
  • [1] Graph deep learning detects contextual prognostic biomarkers from whole-slide images
    Nature Biomedical Engineering, 2022, 6 : 1326 - 1327
  • [2] Derivation of prognostic contextual histopathological features from whole-slide images of tumours via graph deep learning
    Lee, Yongju
    Park, Jeong Hwan
    Oh, Sohee
    Shin, Kyoungseob
    Sun, Jiyu
    Jung, Minsun
    Lee, Cheol
    Kim, Hyojin
    Chung, Jin-Haeng
    Moon, Kyung Chul
    Kwon, Sunghoon
    NATURE BIOMEDICAL ENGINEERING, 2022,
  • [3] Integration of Deep Learning and Graph Theory for Analyzing Histopathology Whole-slide Images
    Jung, Hyun
    Suloway, Christian
    Miao, Tianyi
    Edmondson, Elijah F.
    Morcock, David R.
    Deleage, Claire
    Liu, Yanling
    Collins, Jack R.
    Lisle, Curtis
    2018 IEEE APPLIED IMAGERY PATTERN RECOGNITION WORKSHOP (AIPR), 2018,
  • [4] SliDL: A toolbox for processing whole-slide images in deep learning
    Berman, Adam G.
    Orchard, William R.
    Gehrung, Marcel
    Markowetz, Florian
    PLOS ONE, 2023, 18 (08):
  • [5] Deep Learning Assisted Diagnosis of Onychomycosis on Whole-Slide Images
    Jansen, Philipp
    Creosteanu, Adelaida
    Matyas, Viktor
    Dilling, Amrei
    Pina, Ana
    Saggini, Andrea
    Schimming, Tobias
    Landsberg, Jennifer
    Burgdorf, Birte
    Giaquinta, Sylvia
    Mueller, Hansgeorg
    Emberger, Michael
    Rose, Christian
    Schmitz, Lutz
    Geraud, Cyrill
    Schadendorf, Dirk
    Schaller, Joerg
    Alber, Maximilian
    Klauschen, Frederick
    Griewank, Klaus G.
    JOURNAL OF FUNGI, 2022, 8 (09)
  • [6] Prognostic Gene Expression Profiling in Lung Adenocarcinoma Using Deep Learning Applied to Whole-Slide Images
    Murchan, P.
    Baird, A. -M.
    Broin, P. O.
    Sheils, O.
    Finn, S.
    JOURNAL OF THORACIC ONCOLOGY, 2024, 19 (10) : S164 - S164
  • [7] A pyramidal deep learning pipeline for kidney whole-slide histology images classification
    Abdeltawab, Hisham
    Khalifa, Fahmi
    Mohammed, Mohammed
    Cheng, Liang
    Gondim, Dibson
    El-Baz, Ayman
    SCIENTIFIC REPORTS, 2021, 11 (01)
  • [8] RLogist: Fast Observation Strategy on Whole-Slide Images with Deep Reinforcement Learning
    Zhao, Boxuan
    Zhang, Jun
    Ye, Deheng
    Cao, Jian
    Han, Xiao
    Fu, Qiang
    Yang, Wei
    THIRTY-SEVENTH AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE, VOL 37 NO 3, 2023, : 3570 - 3578
  • [9] A pyramidal deep learning pipeline for kidney whole-slide histology images classification
    Hisham Abdeltawab
    Fahmi Khalifa
    Mohammed Ghazal
    Liang Cheng
    Dibson Gondim
    Ayman El-Baz
    Scientific Reports, 11
  • [10] Deep learning for bone marrow cell detection and classification on whole-slide images
    Wang, Ching-Wei
    Huang, Sheng-Chuan
    Lee, Yu-Ching
    Shen, Yu-Jie
    Meng, Shwu-Ing
    Gaol, Jeff L.
    Medical Image Analysis, 2022, 75