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Dongling Pei

Showing results (11-20 of 21) with videos related to

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Journal of Magnetic Resonance Imaging : JMRI|February 2, 2023
Improving Noninvasive Classification of Molecular Subtypes of Adult Gliomas With Diffusion-Weighted MR Imaging: An Externally Validated Machine Learning AlgorithmYang Guo, Zeyu Ma, Dongling Pei, et al.
CNS Neuroscience & Therapeutics|April 12, 2024
Nuclear autoantigenic sperm protein facilitates glioblastoma progression and radioresistance by regulating the ANXA2/STAT3 axisYuning Qiu, Dongling Pei, Minkai Wang, et al.
European Radiology|February 28, 2023
Radiomic features from dynamic susceptibility contrast perfusion-weighted imaging improve the three-class prediction of molecular subtypes in patients with adult diffuse gliomasDongling Pei, Fangzhan Guan, Xuanke Hong, et al.
Ebiomedicine|September 26, 2021
Deep learning features from diffusion tensor imaging improve glioma stratification and identify risk groups with distinct molecular pathway activitiesJing Yan, Yuanshen Zhao, Yinsheng Chen, et al.
Ebiomedicine|October 23, 2020
Incremental prognostic value and underlying biological pathways of radiomics patterns in medulloblastomaJing Yan, Shenghai Zhang, Kay Ka-Wai Li, et al.
European Radiology|August 24, 2022
Image-based deep learning identifies glioblastoma risk groups with genomic and transcriptomic heterogeneity: a multi-center studyJing Yan, Qiuchang Sun, Xiangliang Tan, et al.
Iscience|January 23, 2025
IDH-mutant glioma risk stratification via whole slide images: Identifying pathological feature associationsXiaotao Wang, Zilong Wang, Weiwei Wang, et al.
Frontiers in Oncology|October 29, 2020
Radiomic Features From Multi-Parameter MRI Combined With Clinical Parameters Predict Molecular Subgroups in Patients With MedulloblastomaJing Yan, Lei Liu, Weiwei Wang, et al.
Nature Communications|October 11, 2023
Neuropathologist-level integrated classification of adult-type diffuse gliomas using deep learning from whole-slide pathological imagesWeiwei Wang, Yuanshen Zhao, Lianghong Teng, et al.
Molecular Cancer|March 7, 2026
Machine learning model on multi-omics data enables risk stratification and identifies molecular heterogeneity and therapeutic targets in glioblastomaZhenyu Zhang, Zilong Wang, Ran Li, et al.
Pageof 3

Showing results (11-20 of 21) with videos related to

Sort By:
Pageof 3
Journal of Magnetic Resonance Imaging : JMRI|February 2, 2023
Improving Noninvasive Classification of Molecular Subtypes of Adult Gliomas With Diffusion-Weighted MR Imaging: An Externally Validated Machine Learning AlgorithmYang Guo, Zeyu Ma, Dongling Pei, et al.
CNS Neuroscience & Therapeutics|April 12, 2024
Nuclear autoantigenic sperm protein facilitates glioblastoma progression and radioresistance by regulating the ANXA2/STAT3 axisYuning Qiu, Dongling Pei, Minkai Wang, et al.
European Radiology|February 28, 2023
Radiomic features from dynamic susceptibility contrast perfusion-weighted imaging improve the three-class prediction of molecular subtypes in patients with adult diffuse gliomasDongling Pei, Fangzhan Guan, Xuanke Hong, et al.
Ebiomedicine|September 26, 2021
Deep learning features from diffusion tensor imaging improve glioma stratification and identify risk groups with distinct molecular pathway activitiesJing Yan, Yuanshen Zhao, Yinsheng Chen, et al.
Ebiomedicine|October 23, 2020
Incremental prognostic value and underlying biological pathways of radiomics patterns in medulloblastomaJing Yan, Shenghai Zhang, Kay Ka-Wai Li, et al.
European Radiology|August 24, 2022
Image-based deep learning identifies glioblastoma risk groups with genomic and transcriptomic heterogeneity: a multi-center studyJing Yan, Qiuchang Sun, Xiangliang Tan, et al.
Iscience|January 23, 2025
IDH-mutant glioma risk stratification via whole slide images: Identifying pathological feature associationsXiaotao Wang, Zilong Wang, Weiwei Wang, et al.
Frontiers in Oncology|October 29, 2020
Radiomic Features From Multi-Parameter MRI Combined With Clinical Parameters Predict Molecular Subgroups in Patients With MedulloblastomaJing Yan, Lei Liu, Weiwei Wang, et al.
Nature Communications|October 11, 2023
Neuropathologist-level integrated classification of adult-type diffuse gliomas using deep learning from whole-slide pathological imagesWeiwei Wang, Yuanshen Zhao, Lianghong Teng, et al.
Molecular Cancer|March 7, 2026
Machine learning model on multi-omics data enables risk stratification and identifies molecular heterogeneity and therapeutic targets in glioblastomaZhenyu Zhang, Zilong Wang, Ran Li, et al.
Pageof 3