Yan‐Jie Shi - Concepedia

Author

Yan‐Jie Shi

Peking University ORCID

Also Known As

Y Shi, Y. Shi, Y.-C. Shi, Ya-Xin Shi, Yan-Jie Shi, Yan-jie Shi, Yanjie Shi, Yan‐Jie Shi

Publications

1.1K

Citations

H-Index

Concepts

All Affiliations

Peking University Peking University Cancer Hospital Ministry of Education University of Chinese Academy of Sciences

About

Yan‐Jie Shi is an author at Peking University specializing in radiation oncology, radiology, and health sciences.

Top Concepts

#	Concept	H-Index	Publications	Citations
1	Health Sciences	3	3	172
2	Medicine	2	2	139
3	Engineering	1	1	33
4	Radiation Medicine	1	1	112
5	Surgical Oncology	1	1	112

Yan‐Jie Shi

Publications

Citations

H-Index

Page 1

	Year	Citations
Radiomics Analysis for Evaluation of Pathological Complete Response to Neoadjuvant Chemoradiotherapy in Locally Advanced Rectal Cancer Zhenyu Liu, Xiaoyan Zhang, Yan‐Jie Shi, Clinical Cancer Research	2017	548
MRI of Extramural Venous Invasion in Locally Advanced Rectal Cancer: Relationship to Tumor Recurrence and Overall Survival Xiaoyan Zhang, Shuai Wang, Xiao-Ting Li, Radiology Surgical OncologyTumor InnervationColorectal SurgeryTumor RecurrenceMultimodality	2018	112
Predicting Rectal Cancer Response to Neoadjuvant Chemoradiotherapy Using Deep Learning of Diffusion Kurtosis MRI Xiaoyan Zhang, Lin Wang, Haitao Zhu, Radiology	2020	108
Radiomics Analysis Based on Diffusion Kurtosis Imaging and T2 Weighted Imaging for Differentiation of Pancreatic Neuroendocrine Tumors From Solid Pseudopapillary Tumors Yan‐Jie Shi, Haitao Zhu, Yuliang Liu, Frontiers in Oncology	2020	37
Quantitative analysis of diffusion weighted imaging to predict pathological good response to neoadjuvant chemoradiation for locally advanced rectal cancer Zhenchao Tang, Xiaoyan Zhang, Zhenyu Liu, Radiotherapy and Oncology Pathological Good ResponseNeoadjuvant ChemoradiationEngineeringOncologic ImagingMedical Imaging	2018	33
Prediction of pathological nodal stage of locally advanced rectal cancer by collective features of multiple lymph nodes in magnetic resonance images before and after neoadjuvant chemoradiotherapy Haitao Zhu, Xiaoyan Zhang, Xiao-Ting Li, Chinese Journal of Cancer Research	2019	29
Differential diagnosis of hemangiomas from spinal osteolytic metastases using 3.0 T MRI: comparison of T1-weighted imaging, chemical-shift imaging, diffusion-weighted and contrast-enhanced imaging Yan‐Jie Shi, Xiao-Ting Li, Xiaoyan Zhang, Oncotarget T MriOncologic ImagingFat SuppressionSpinal OncologyMagnetic Resonance Imaging	2017	27
Automatic segmentation of rectal tumor on diffusion‐weighted images by deep learning with U‐Net Hai‐Tao Zhu, Xiaoyan Zhang, Yan‐Jie Shi, Journal of Applied Clinical Medical Physics	2021	27
Deep learning model improves radiologists’ performance in detection and classification of breast lesions Ying‐Shi Sun, Yu‐Hong Qu, Dong Wang, Chinese Journal of Cancer Research	2021	23
A Deep Learning Model to Predict the Response to Neoadjuvant Chemoradiotherapy by the Pretreatment Apparent Diffusion Coefficient Images of Locally Advanced Rectal Cancer Haitao Zhu, Xiaoyan Zhang, Yan‐Jie Shi, Frontiers in Oncology	2020	17

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