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Chaofeng Li

Showing results (141-150 of 152) with videos related to

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Oral Oncology|May 23, 2021
An interpretable machine learning prognostic system for locoregionally advanced nasopharyngeal carcinoma based on tumor burden featuresXi Chen, Yingxue Li, Xiang Li, et al.
Frontiers in Oncology|October 12, 2020
Prognostic and Treatment Guiding Significance of MRI-Based Tumor Burden Features and Nodal Necrosis in Nasopharyngeal CarcinomaXi Chen, Xun Cao, Bingzhong Jing, et al.
Journal of the National Cancer Institute|September 24, 2020
A Prognostic Predictive System Based on Deep Learning for Locoregionally Advanced Nasopharyngeal CarcinomaMengyun Qiang, Chaofeng Li, Yuyao Sun, et al.
Science Translational Medicine|January 3, 2020
Circulating tumor DNA methylation profiles enable early diagnosis, prognosis prediction, and screening for colorectal cancerHuiyan Luo, Qi Zhao, Wei Wei, et al.
Gigascience|January 7, 2020
Chromosome-level genome assembly reveals the unique genome evolution of the swimming crab (Portunus trituberculatus)Boping Tang, Daizhen Zhang, Haorong Li, 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.
The Lancet. Digital Health|December 25, 2021
Development and validation of a radiopathomics model to predict pathological complete response to neoadjuvant chemoradiotherapy in locally advanced rectal cancer: a multicentre observational studyLili Feng, Zhenyu Liu, Chaofeng Li, et al.
Neuro-Oncology|January 31, 2022
Development and validation of a deep-learning model for detecting brain metastases on 3D post-contrast MRI: a multi-center multi-reader evaluation studyShaohan Yin, Xiao Luo, Yadi Yang, 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 16

Showing results (141-150 of 152) with videos related to

Sort By:
Pageof 16
Oral Oncology|May 23, 2021
An interpretable machine learning prognostic system for locoregionally advanced nasopharyngeal carcinoma based on tumor burden featuresXi Chen, Yingxue Li, Xiang Li, et al.
Frontiers in Oncology|October 12, 2020
Prognostic and Treatment Guiding Significance of MRI-Based Tumor Burden Features and Nodal Necrosis in Nasopharyngeal CarcinomaXi Chen, Xun Cao, Bingzhong Jing, et al.
Journal of the National Cancer Institute|September 24, 2020
A Prognostic Predictive System Based on Deep Learning for Locoregionally Advanced Nasopharyngeal CarcinomaMengyun Qiang, Chaofeng Li, Yuyao Sun, et al.
Science Translational Medicine|January 3, 2020
Circulating tumor DNA methylation profiles enable early diagnosis, prognosis prediction, and screening for colorectal cancerHuiyan Luo, Qi Zhao, Wei Wei, et al.
Gigascience|January 7, 2020
Chromosome-level genome assembly reveals the unique genome evolution of the swimming crab (Portunus trituberculatus)Boping Tang, Daizhen Zhang, Haorong Li, 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.
The Lancet. Digital Health|December 25, 2021
Development and validation of a radiopathomics model to predict pathological complete response to neoadjuvant chemoradiotherapy in locally advanced rectal cancer: a multicentre observational studyLili Feng, Zhenyu Liu, Chaofeng Li, et al.
Neuro-Oncology|January 31, 2022
Development and validation of a deep-learning model for detecting brain metastases on 3D post-contrast MRI: a multi-center multi-reader evaluation studyShaohan Yin, Xiao Luo, Yadi Yang, 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 16