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HRA005239
   HRA005239.xlsx
Title:
Neuropathologist-level integrated classification of adult-type diffuse gliomas using deep learning from whole-slide pathological images
Release date:
2023-10-08
Description:
Current diagnosis of glioma types requires combining both histological features and molecular characteristics, which is an expensive and time-consuming procedure. Determining the tumor types directly from whole-slide images (WSIs) is of great value for glioma diagnosis. This study presents an integrated diagnosis model for automatic classification of diffuse gliomas from annotation-free standard WSIs.
Data Accessibility:   
Controlled access Request Data
BioProject:
PRJCA018731
Study type:
Disease Study
Disease name:
brain glioma
Data Access Committee

For each controlled access study, there is a corresponding Data Access Committee(DAC) to determine the access permissions. Access to actual data files is not managed by NGDC.


DAC NO.:
HDAC002910
DAC name:
Neurosurgery
Contact person:
Zhang Zhenyu
Email:
fcczhangzy1@zzu.edu.cn
Description:
Department of Neurosurgery, The First Affiliated Hospital of Zhengzhou University
Individuals & samples
Files
Request Data
Submitter:   Zhang Zhenyu / fcczhangzy1@zzu.edu.cn
Organization:   The First Affiliated Hospital of Zhengzhou University
Submission date:   2023-08-08
Requests:   -