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Academic Radiology|April 9, 2026
Multiparametric MRI-Based Integrated Analysis of Clinical, Radiomics, Deep Learning, and Machine Learning for Predicting Tumor Proliferation and Prognosis in Locally Advanced Rectal CancerZhiheng Li, Huizhen Huang, Rongzhi Cai, et al.
European Journal of Radiology|May 22, 2025
Comparison of clinical, radiomics, deep learning, and fusion models for predicting early recurrence in locally advanced rectal cancer based on multiparametric MRI: a multicenter studyZhiheng Li, Yangyang Qin, Xiaoqing Liao, et al.
Frontiers in Oncology|February 9, 2023
1H NMR-based metabolomics of paired tissue, serum and urine samples reveals an optimized panel of biofluids metabolic biomarkers for esophageal cancerTing Ouyang, Changchun Ma, Yan Zhao, et al.
NPJ Precision Oncology|March 6, 2026
Integration of radiomics, deep learning, transcriptomics, and metabolomics reveals prognostic risk stratification and underlying biological mechanisms in colorectal cancerZhiheng Li, Rongzhi Cai, Yangyang Qin, et al.
International Journal of Cancer|December 4, 2024
NMR-based metabolomics combined with metabolic pathway analysis reveals metabolic heterogeneity of colorectal cancer tissue at different anatomical locations and stagesRongzhi Cai, LiXin Ke, Yan Zhao, et al.
ACS Chemical Neuroscience|November 30, 2024
Visualization of Unconjugated Bilirubin In Vivo with a Novel Approach Using Chemical Exchange Saturation Transfer Magnetic Resonance Imaging in a Rat ModelLin Yang, Yan Cheng, Yanlong Jia, et al.
Nature Communications|March 20, 2024
NMR and MS reveal characteristic metabolome atlas and optimize esophageal squamous cell carcinoma early detectionYan Zhao, Changchun Ma, Rongzhi Cai, et al.
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