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Yishu Deng

Showing results (31-40 of 39) with videos related to

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Cancer Imaging : the Official Publication of the International Cancer Imaging Society|March 25, 2025
Establishment of a deep-learning-assisted recurrent nasopharyngeal carcinoma detecting simultaneous tactic (DARNDEST) with high cost-effectiveness based on magnetic resonance images: a multicenter study in an endemic areaYishu Deng, Yingying Huang, Haijun Wu, et al.
European Journal of Radiology|September 18, 2023
Deep learning-based recurrence detector on magnetic resonance scans in nasopharyngeal carcinoma: A multicenter studyYishu Deng, Yingying Huang, Bingzhong Jing, et al.
Cancer Cell International|December 3, 2025
AI-based neoadjuvant immunotherapy response prediction across pan-cancer: a comprehensive reviewYishu Deng, Tailin Li, Yunze Wang, et al.
European Journal of Radiology|September 30, 2025
Modifying node-RADS in diagnosing parotid lymph node metastasis of nasopharyngeal carcinomaDongxia He, Hu Liang, Yishu Deng, et al.
Medicine|August 24, 2019
CTPA, DECT, MRI, V/Q Scan, and SPECT/CT V/Q for the noninvasive diagnosis of chronic thromboembolic pulmonary hypertension: A protocol for systemic review and network meta-analysis of diagnostic test accuracyShuanglan Xu, Jiao Yang, Yun Zhu, et al.
Journal of Translational Medicine|November 25, 2025
Radiology-based artificial intelligence for predicting targeted therapy response in pan-cancer: a comprehensive reviewBo Yang, Silin Chen, Yunze Wang, et al.
Iscience|February 29, 2024
An interpretable deep learning model for identifying the morphological characteristics of dMMR/MSI-H gastric cancerXueyi Zheng, Bingzhong Jing, Zihan Zhao, et al.
Cell Reports. Medicine|May 2, 2024
Artificial intelligence for diagnosis and prognosis prediction of natural killer/T cell lymphoma using magnetic resonance imagingYuChen Zhang, YiShu Deng, QiHua Zou, et al.
The Lancet. Oncology|October 9, 2019
Real-time artificial intelligence for detection of upper gastrointestinal cancer by endoscopy: a multicentre, case-control, diagnostic studyHuiyan Luo, Guoliang Xu, Chaofeng Li, et al.
Pageof 4

Showing results (31-40 of 39) with videos related to

Sort By:
Pageof 4
You have reached the last page of results.This site can display upto 39 results.
Cancer Imaging : the Official Publication of the International Cancer Imaging Society|March 25, 2025
Establishment of a deep-learning-assisted recurrent nasopharyngeal carcinoma detecting simultaneous tactic (DARNDEST) with high cost-effectiveness based on magnetic resonance images: a multicenter study in an endemic areaYishu Deng, Yingying Huang, Haijun Wu, et al.
European Journal of Radiology|September 18, 2023
Deep learning-based recurrence detector on magnetic resonance scans in nasopharyngeal carcinoma: A multicenter studyYishu Deng, Yingying Huang, Bingzhong Jing, et al.
Cancer Cell International|December 3, 2025
AI-based neoadjuvant immunotherapy response prediction across pan-cancer: a comprehensive reviewYishu Deng, Tailin Li, Yunze Wang, et al.
European Journal of Radiology|September 30, 2025
Modifying node-RADS in diagnosing parotid lymph node metastasis of nasopharyngeal carcinomaDongxia He, Hu Liang, Yishu Deng, et al.
Medicine|August 24, 2019
CTPA, DECT, MRI, V/Q Scan, and SPECT/CT V/Q for the noninvasive diagnosis of chronic thromboembolic pulmonary hypertension: A protocol for systemic review and network meta-analysis of diagnostic test accuracyShuanglan Xu, Jiao Yang, Yun Zhu, et al.
Journal of Translational Medicine|November 25, 2025
Radiology-based artificial intelligence for predicting targeted therapy response in pan-cancer: a comprehensive reviewBo Yang, Silin Chen, Yunze Wang, et al.
Iscience|February 29, 2024
An interpretable deep learning model for identifying the morphological characteristics of dMMR/MSI-H gastric cancerXueyi Zheng, Bingzhong Jing, Zihan Zhao, et al.
Cell Reports. Medicine|May 2, 2024
Artificial intelligence for diagnosis and prognosis prediction of natural killer/T cell lymphoma using magnetic resonance imagingYuChen Zhang, YiShu Deng, QiHua Zou, et al.
The Lancet. Oncology|October 9, 2019
Real-time artificial intelligence for detection of upper gastrointestinal cancer by endoscopy: a multicentre, case-control, diagnostic studyHuiyan Luo, Guoliang Xu, Chaofeng Li, et al.
Pageof 4